Selected Papers by
Topics
My Google
Citation Profile:
http://scholar.google.com/citations?user=tAK5l1IAAAAJ
Newly
accepted:
[1] R. Wu, L. Sun, Z. Ma, L. Zhang,
"One-Step Effective Diffusion Network for Real-World Image
Super-Resolution," in NeurIPS 2024. (paper) (code) (High quality and stable super-resolution
in just one step diffusion!) |
[2] G. Zhang, L. Fan, C. He, Z. Lei, Z.
Zhang, L. Zhang, "Voxel Mamba: Group-Free State Space Models for Point
Cloud based 3D Object Detection," in NeurIPS 2024 (spotlight). (paper) (code) (New SOTA on point cloud 3D detection!) |
[3] Y. Zhang, L. Zhang, "AdaNeg:
Adaptive Negative Proxy Guided OOD Detection with Vision-Language
Models," in NeurIPS 2024. (paper) (code) (New SOTA on OOD detection!) |
[4]
D.
Chen, Z. Zhang, J. Liang, L. Zhang, "SSL: A Self-similarity Loss for
Improving Generative Image Super-resolution," in ACM MM 2024. (paper) (code) (A simple yet effective loss for generative
SR!) |
Major Conference Papers:
ECCV
2024
|
SIGGRAPH 2024
[17] J. Li, L. Wang, L. Zhang, B. Wang, "TensoSDF:
Roughness-aware Tensorial Representation for Robust Geometry and Material
Reconstruction," ACM Transactions on Graphics (Proceedings of
SIGGRAPH 2024). (paper) (code) |
CVPR
2024
[18] M. Li, S. Li, X. Zhang, L. Zhang, "UniVS:
Unified and Universal Video Segmentation with Prompts as Queries," in
CVPR 2024. (paper) (code) |
[19] Y. Yuan, W. Li, J. Liu, D. Tang, X. Luo,
C. Qin, L. Zhang and J. Zhu, "Osprey: Pixel Understanding with Visual
Instruction Tuning," in CVPR 2024. (paper) (code) |
[20] R. Wu, T. Yang, L. Sun, Z. Zhang, S. Li,
L. Zhang, "SeeSR: Towards Semantics-Aware Real-World Image
Super-Resolution," in CVPR 2024. (paper) (code) (See also the related work of PASD.) |
[21] Y. Zhang, W. Zhu, H. Tang, Z. Ma, K.
Zhou, L. Zhang, "Dual Memory Networks: A Versatile Adaptation Approach
for Vision-Language Models," in CVPR 2024. (paper) (code) |
[22] J. Li, Z. Chen, X. Wu, L. Wang, B. Wang,
L. Zhang, "Neural Super-Resolution for Real-time Rendering with Radiance
Demodulation," in CVPR 2024. (paper) (code) |
NeurISP
2023
[23] W. Li, Y. Yuan, S. Wang, W. Liu, D. Tang,
J. Liu, J. Zhu, L. Zhang, "Label-efficient Segmentation via Affinity
Propagation," in NeurIPS 2023. (paper) (code) |
ICCV
2023
[24] Y. Wei, Y. Zhang, Z. Ji, J. Bai, L.
Zhang, W. Zuo, "ELITE: Encoding Visual Concepts into Textual Embeddings
for Customized Text-to-Image Generation," in ICCV 2023. (paper) (supp) (code) (Oral presentation) |
[25] J. Ma, Z. Liang, W. Xiang, X. Yang, L.
Zhang, "A Benchmark for Chinese-English Scene Text Image
Super-resolution," in ICCV 2023. (paper) (supp) (code&dataset)
[26] W. Li, Y. Yuan, S. Wang, J. Zhu, J. Li,
J. Liu, L. Zhang, "Point2Mask: Point-supervised Panoptic Segmentation
via Optimal Transport," in ICCV 2023. (paper) (supp) (code) |
[27] W. Xiang, C. Li, Y.
Zhou, B. Wang, L. Zhang, "Generative Action Description Prompts for
Skeleton-based Action Recognition," in ICCV 2023. (paper) (supp) (code) |
[28] L. Chen, C. Lei, R. Li, S. Li, Z. Zhang,
L. Zhang, "FPR: False Positive Rectification for Weakly Supervised
Semantic Segmentation," in ICCV 2023. (paper) (code) |
[29] Y. Yuan, Y. Wang, L. Wang, X. Zhao, H.
Lu, Y. Wang, W. Su, L. Zhang, "Isomer: Isomerous Transformer for
Zero-shot Video Object Segmentation," in ICCV 2023. (paper) (code) |
SIGGRAPH ASIA
2023
[30] Y. Cui, G. Pan, J. Yang, L. Zhang, L.
Yan, B. Wang, "Multiple-bounce Smith Microfacet BRDFs using the
Invariance Principle," Siggraph Asia 2023. (paper) (supp) (code) |
CVPR
2023
[31] H. Yong, Y. Sun, L. Zhang, "A General
Regret Bound of Preconditioned Gradient Method for DNN Training," in
CVPR 2023. (paper) (supp) (code) (Highlight paper) |
[32] C. He, R. Li, Y. Zhang, S. Li, L. Zhang,
"MSF: Motion-guided Sequential Fusion for Efficient 3D Object Detection
from Point Cloud Sequences," in CVPR 2023. (paper) (code) |
[33] M. Li, S. Li, W. Xiang, L. Zhang,
"MDQE: Mining Discriminative Query Embeddings to Segment Occluded
Instances on Challenging Videos," in CVPR 2023. (paper) (supp) (code) |
[34] D. Chen, J. Liang, X. Zhang, M. Liu, H.
Zeng, L. Zhang, "Human Guided Ground-truth Generation for Realistic
Image Super-resolution," in CVPR 2023. (paper) (supp) (dataset&code) |
[35] S. Liu, X. Zhang, H. Zeng, L. Sun, Z.
Liang, L. Zhang, "Joint HDR Denoising and Fusion: A Real-World Mobile
HDR Image Dataset," in CVPR 2023. (paper) (supp) (dataset&code) |
[36] Z. Ma, X. Zhu, G-J. Qi, Z. Lei, Lei
Zhang, "OTAvatar: One-shot Talking Face Avatar with Controllable
Tri-plane Rendering," in CVPR 2023. (paper) (supp) (code) |
[37] R. Li, C. He, Y. Zhang, S. Li, L. Chen,
L. Zhang, "SIM: Semantic-aware Instance Mask Generation for
Box-Supervised Instance Segmentation," in CVPR 2023. (paper) (code) |
[38] R. Li, S. Li, C. He, Y. Zhang, L. Zhang,
"DynaMask: Dynamic Mask Selection for Instance Segmentation," in
CVPR 2023. (paper) (code) |
[39] S. Li, M. Li, R. Li, C. He, L. Zhang,
"One-to-Few Label Assignment for End-to-End Dense Detection," in
CVPR 2023. (paper) (supp) (code) |
[40] P. Wang, Z. Zhang, Z. Lei, L. Zhang,
"Sharpness-Aware Gradient Matching for Domain Generalization," in
CVPR 2023. (paper) (supp) (code) |
[41] Y. Wei, Z. Ji, X. Wu, J. Bai, L. Zhang,
W. Zuo, "Inferring and Leveraging Parts from Object Shape for Improving
Semantic Image Synthesis," in CVPR 2023. (paper) (supp) (code) |
ECCV
2022
[42] X. Zhang, H. Zeng, S. Guo, L. Zhang, "Efficient Long-Range
Attention Network for Image Super-resolution," in ECCV 2022. (paper) (supp) (code) (An
effective and efficient transformer architecture for image restoration.) |
[43] J. Liang, H. Zeng, L. Zhang, "Efficient and Degradation-Adaptive
Network for Real-World Image Super-Resolution," in ECCV 2022. (paper) (supp) (code) (Toward
more practical and effective real-world super-resolution.) |
[44] H. Yong and L.
Zhang, "An Embedded Feature Whitening
Approach to Deep Neural Network Optimization," in ECCV 2022.
(paper) (supp) (code) (To
make feature whitening much more practical for DNN optimization.) |
[45] W. Xiang, C.
Li, X. Wei, B. Wang, L. Zhang, "Spatiotemporal Self-attention
Modeling with Temporal Patch Shift for Action Recognition," in ECCV 2022. (paper) (supp) (code) (A simple yet effective self-attention model for
video based action recognition.) |
[46] W. Li, W. Liu,
J. Zhu, M. Cui, X. Hua, L. Zhang, "Box-supervised
Instance Segmentation with Level Set Evolution," in ECCV 2022.
(paper) (code) (New
state-of-the-art for box-supervised instance segmentation.) |
[47] H. Zheng, H. Yong, L. Zhang, "Unfolded Deep Kernel Estimation for
Blind Image Super-resolution," in ECCV 2022. (paper) (supp) (code) (The
first explicit unfolding solution for deep kernel estimation.) |
[48] X. Li, C. Chen,
X. Lin, W. Zuo, L. Zhang, "From Face to
Natural Image: Learning Real Degradation for Blind Image Super-Resolution," In ECCV 2022. (paper) (supp) (code) (Transfer facial image priors to natural image
restoration.) |
CVPR
2022
[49] J. Liang, H.
Zeng, L. Zhang, "Details or Artifacts: A Locally
Discriminative Learning Approach to Realistic Image Super-Resolution," in CVPR 2022. (oral
presentation) (paper) (code) (We
make the GAN-based super-resolution models much more robust!) |
[50] Y. Zhang, M.
Li, R. Li, K. Jia, L. Zhang, "Exact Feature
Distribution Matching for Arbitrary Style Transfer and Domain Generalization," in CVPR 2022. (oral presentation) (paper) (code) (A
simple yet very effective step toward feature statistics learning.) |
[51] S. Li, C. He,
R. Li, L. Zhang, "A Dual Weighting
Label Assignment Scheme for Object Detection," in CVPR 2022.
(paper) (code) (A
flexible weighting scheme to both positive and negative samples.) |
[52] B. Chen, P. Li,
X. Chen, B. Wang, L. Zhang, X-S. Hua, "Dense Learning
based Semi-Supervised Object Detection," in CVPR 2022.
(paper) (code) (The first anchor-free semi-supervised object
detector.) |
[53] C. He, L.
Zhang, "Voxel Set Transformer: A Set-to-Set
Approach to 3D Object Detection from Point Clouds," in CVPR 2022.
(paper) (code) (A set-to-set transformer built upon voxel.) |
[54] R. Li, S. Li,
C. He, Y. Zhang, X. Jia, L. Zhang, "Class-Balanced
Pixel-Level Self-Labeling for Domain Adaptive Semantic Segmentation," in CVPR 2022. (paper) (code) |
[55] S. Guo, X.
Yang, J. Ma, G. Ren, L. Zhang, "A Differentiable
Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift," in CVPR 2022. (paper) (code) |
[56] J. Ma, Z.
Liang, L. Zhang, "A Text
Attention Network for Spatial Deformation Robust Scene Text Image
Super-resolution," in CVPR 2022.
(paper) (code) |
[57] Z. Yue, Q.
Zhao, J. Xie, L. Zhang, D. Meng, Kwan-Yee K. Wong, "Blind Image Super-resolution with Elaborate Degradation Modeling on
Noise and Kernel," in CVPR 2022.
(paper) (code) |
AAAI
2022
[58] W. Liu, G. Ren, R. Yu, S. Guo, J. Zhu, L. Zhang, "Image-Adaptive
YOLO for Object Detection in Adverse Weather Conditions," in AAAI 2022. (paper) (supp) (code) (Adaptively enhance the image for better object
detection in bad weather!) |
ACM
MM 2021
[59] X. Zhang, H.
Zeng, L. Zhang, "Edge-oriented Convolution Block for Real-time Super
Resolution on Mobile Devices," in ACM Multimedia 2021. (oral) (paper) (code) (Make real-time video super-resolution on mobile
devices possible!) |
ICCV
2021
[60] X. Yang, W.
Xiang, H. Zeng, L. Zhang, "Real-world Video Super-resolution: A
Benchmark Dataset and A Decomposition based Learning Scheme," in ICCV
2021. (paper) (dataset&code) (The first real-world video super-resolution
dataset!) |
[61] G. Chen, C.
Chen, S. Guo, Z. Liang, K-Y. Wong, L. Zhang, "HDR Video Reconstruction:
A Coarse-to-fine Network and A Real-world Benchmark Dataset," in ICCV
2021. (paper) (dataset&code) (A large-scale real-world HDR video reconstruction
dataset!) |
[62] J. Tang, J.
Lei, D. Xu, F. Ma, K. Jia, L. Zhang, "Sign-Agnostic CONet: Learning
Implicit Surface Reconstructions by Sign-Agnostic Optimization of
Convolutional Occupancy Networks," in ICCV 2021. (oral) (paper) (code) |
[63] B. Chen, Z.
Yan, K. Li, P. Li, B. Wang, W. Zuo, L. Zhang, "Variational Attention:
Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd
Counting," in ICCV 2021. (paper) |
CVPR
2021
[64] H. Zheng, H. Yong, L. Zhang, "Deep
Convolutional Dictionary Learning for Image Denoising," in CVPR 2021. (paper) (supp) (code) (What is the limit
of image denoising? We just go one step further.) |
[65] T. Yang, P. Ren, X. Xie, L. Zhang,
"GAN Prior Embedded Network for Blind Face Restoration in the
Wild," in CVPR 2021. (paper) (supp) (code) (Robust face image enhancement in the wild!) (Training code was released!) |
[66] J. Liang, H. Zeng, L. Zhang,
"High-Resolution Photorealistic Image Translation in Real-Time: A
Laplacian Pyramid Translation Network," in CVPR 2021. (paper) (supp) (code) (4K I2I in real time!) |
[67] J. Liang, H. Zeng, M. Cui, X. Xie, L.
Zhang, "PPR10K: A Large-Scale Portrait Photo Retouching Dataset with
Human-Region Mask and Group-Level Consistency," in CVPR 2021. (paper) (supp) (code) (The first large-scale
portrait photo retouching dataset!) |
[68] M. Li, S. Li, L. Li, and L. Zhang,
"Spatial Feature Calibration and Temporal Fusion for Effective One-stage
Video Instance Segmentation," in CVPR 2021. (paper) (supp) (code) |
[69] Q. Yang, X. Wei, B. Wang, X-S. Hua, L.
Zhang, "Interactive Self-Training with Mean Teachers for Semi-Supervised
Object Detection," in CVPR 2021. (paper) (code) |
[70] C. Chen, X. Li, L. Yang, X. Lin, L.
Zhang, K-Y. Wong, "Progressive Semantic-Aware Style Transformation for
Blind Face Restoration," in CVPR 2021. (paper) (code) |
[71] J. Tang, D. Xu, F. Ma, K. Jia, L. Zhang,
"Learning Parallel Dense Correspondence from Spatio-Temporal Descriptors
for Efficient and Robust 4D Reconstruction," in CVPR 2021. (paper) (code) |
[72] P. Li, B. Wang, L. Zhang, "Virtual
Fully-Connected Layer: Training Large-scale Face Recognition Dataset with
Limited Computational Resources," in CVPR 2021. (paper) (supp) (code) |
[73] W. Li, T. Guo, P. Li, B. Chen, B. Wang,
W. Zuo, L. Zhang, "VirFace: Enhancing Face Recognition via Unlabeled
Shallow Data," in CVPR 2021. (paper) (supp) (code) |
AAAI
2021
[74] S. Li, J. Huang, X-S. Hua, L. Zhang,
"Category Dictionary Guided Unsupervised Domain Adaptation for Object
Detection", in AAAI 2021. (paper) (code) |
ACCV
2020
[75] J. Xiao, H. Yong, L. Zhang,
"Degradation Model Learning for Real-World Single Image
Super-resolution," in ACCV2020. (paper) (code) |
[76] W. Xiang, J. Huang, X-S. Hua, L. Zhang,
"Part-aware Attention Network for Person Re-Identification," in
ACCV 2020. (paper) (code) |
[77] W. Xiang, H. Yong, J. Huang, X-S. Hua, L.
Zhang, "Second-order Camera-aware Color Transformation for Cross-domain
Person Re-identification," in ACCV 2020. (paper) (code) |
ACM
MM 2020
[78] H. Zheng, W.
Zuo, L. Zhang, "BS-MCVR: Binary-sensing based Mobile-cloud Visual
Recognition," in ACM Multimedia 2020. (oral) (paper) (code) (Toward a binary-sensing
camera for future visual recognition!) |
ECCV
2020
[79] H. Yong, J.
Huang, X. Hua, L. Zhang, "Gradient Centralization: A New Optimization
Technique for Deep Neural Networks," in ECCV 2020. (oral) (paper) (supp) (code) (One line of code to improve DNN
optimization!) |
[80] L. Li, K. Wang,
S. Li, X. Feng, L. Zhang, "LST-Net: Learning a Convolutional Neural
Network with a Learnable Sparse Transform," in ECCV 2020. (paper) (supp) (code) (A new bottleneck for learning
efficient and effective CNNs!) |
[81] Z. Liang, S.
Guo, H. Gu, H. Zhang, L. Zhang, "A Decoupled Learning Scheme for
Real-world Burst Denoising from Raw Images," in ECCV 2020. (paper) (supp) (code) (A novel learning scheme for
real-world burst denoising!) |
[82] H. Yong, J.
Huang, D. Meng, X. Hua, L. Zhang, "Momentum Batch Normalization for Deep
Learning with Small Batch Size," in ECCV 2020. (paper) (supp) (code) |
[83] Z. Yue, Q.
Zhao, L. Zhang, D. Meng, "Dual Adversarial Network: Toward Real Noise
Removal and Noise Generation," in ECCV 2020. (paper) (code) |
[84] X. Li, C. Chen,
S. Zhou, X. Lin, W. Zuo, L. Zhang, "Blind Face Restoration via Deep
Multi-scale Component Dictionaries," in ECCV 2020. (paper) (code) |
[85] Y. Zhang, B.
Deng, K. Jia, L. Zhang, "Label Propagation with Augmented Anchors: A
Simple Semi-Supervised Learning Baseline for Unsupervised Domain
Adaptation," in ECCV 2020. (spotlight) (paper) (code) |
[86] X. Zhao, Y.
Pang, L. Zhang, H. Lu, L. Zhang, "Suppress and Balance: A Simple Gated
Network for Salient Object Detection," in ECCV 2020. (oral) (paper) (code) |
[87] X. Zhao, L. Zhang,
Y. Pang, H. Lu, L. Zhang, "A Single Stream Network for Robust and
Real-time RGB-D Salient Object Detection," in ECCV 2020. (paper) (code) |
CVPR
2020
[88] C. He, H. Zeng,
J. Huang, X. Hua, L. Zhang, "Structure Aware Single-stage 3D Object
Detection from Point Cloud," in CVPR 2020. (paper) (code) |
[89] J. Xiao*, S.
Gu*, L. Zhang, "Multi-Domain Learning for Accurate and Few-Shot Color
Constancy," in CVPR 2020. (paper) (code) (*The first two authors contributed
equally to this work.) |
NeurISP
2019
[90] Z. Yue, H.
Yong, Q. Zhao, L. Zhang, D. Meng, "Variational Denoising Network: Toward
Blind Noise Modeling and Removal," NeurIPS
2019. (paper) (code) |
ICCV
2019
[91] J. Cai*, H. Zeng*, H. Yong, Z. Cao, L.
Zhang, "Toward Real-World Single Image Super-Resolution: A New Benchmark
and A New Model," in ICCV 2019
(oral). (paper) (supp) (code) (*The first two authors contributed
equally to this work.) |
[92] S. Li, L. Yang, J. Huang, X. Hua, L.
Zhang, "Dynamic Anchor Feature Selection for Single-Shot Object
Detection", in ICCV 2019. (paper) (code) |
CVPR
2019
[93] Hui Zeng, Lida Li, Zisheng Cao, Lei Zhang,
"Reliable and Efficient Image Cropping: A Grid Anchor based
Approach," in CVPR 2019. (paper) (supp) (code&dataset) (A totally new framework for
image cropping with a large scale dataset!) |
[94] Xixi Jia, Sanyang Liu, Xiagnchu Feng, Lei Zhang,
"FOCNet: A Fractional Optimal Control Network for Image Denoising,"
in CVPR 2019. (paper) (code) |
[95] Kai Zhang, Wangmeng Zuo, Lei Zhang, "Deep
Plug-and-Play Super-Resolution for Arbitrary Blur Kernels," in CVPR
2019. (paper) (code) |
[96] Shi Guo, Wangmeng Zuo, Zifei Yan, Kai Zhang, Lei
Zhang, "Toward Convolutional Blind Denoising of Real-world Noisy
Photographs," in CVPR 2019. (paper) (supp) (code) |
[97] Tao Dai, Jianrui Cai, Yongbing Zhang, Shutao Xia,
Lei Zhang, "Second-order Attention Network for Single Image
Super-resolution," in CVPR 2019 (oral). (paper) (supp) (code) |
AAAI
2019
[98] L. Yang, D.
Zhang, L. Zhang, "Learning a Visual Tracker from a Single Movie without
Human Annotation," AAAI 2019. (paper) (code) |
ECCV
2018
[99] J. Xu, L. Zhang, D. Zhang, "A
Trilateral Weighted Sparse Coding Scheme for Real-World Image
Denoising," in ECCV 2018.
(paper, supp) (code) |
[100] S. Cai, W. Zuo, L. Davis, L. Zhang, "Weakly-supervised
Video Summarization using Variational Encoder-Decoder and Web Prior," in
ECCV 2018. (paper) (code) |
CVPR
2018
[101] W.
An, H. Wang, Q. Sun, J. Xu, Q. Dai, L. Zhang, "A PID Controller Approach
for Stochastic Optimization of Deep Networks," in CVPR 2018. (Spotlight paper)
(paper, supp) (code) (We, for the first time,
connect classical control theory with deep network optimization, and improve
up to 50% the efficiency over SGD-Momentum!) |
[102] Z.
Liang, J. Xu, D. Zhang, Z. Cao, L. Zhang, "A Hybrid L1-L0
Layer Decomposition Model for Tone Mapping," in CVPR 2018. (paper, supp) (code) |
[103] K.
Zhang, W. Zuo, L. Zhang, "Learning a Single Convolutional
Super-Resolution Network for Multiple Degradations," in CVPR 2018. (paper) (code) |
[104] F.
Li, C. Tian, W. Zuo, L. Zhang, M-H. Yang, "Learning Spatial-Temporal
Regularized Correlation Filters for Visual Tracking," in CVPR 2018. (paper, supp) (code) |
[105] K.
Wang, X. Yan, D. Zhang, L. Zhang, L. Lin, "Towards Human-Machine
Cooperation: Self-supervised Sample Mining for Object Detection," in
CVPR 2018. (paper) (code) |
AAAI
2018
[106] T.
Chen, Liang Lin, W. Zuo, X. Luo, L. Zhang, "Learning a Wavelet-Like
Auto-encoder to Accelerate Deep Neural Networks," AAAI 2018. (paper) (code) |
ICCV
2017
[107] J.
Xu, L. Zhang, D. Zhang, X. Feng, "Multi-channel Weighted Nuclear Norm
Minimization for Real Color Image Denoising," 2017 International Conference on Computer Vision (ICCV 2017). (paper, supp) (code) |
[108] S.
Cai, W. Zuo, L. Zhang, "Higher-order Integration of Hierarchical
Convolutional Activations for Fine-grained Visual Categorization," 2017 International Conference on Computer
Vision (ICCV 2017). (paper) (code) |
[109] S.
Gu, D. Meng, W. Zuo, L. Zhang, "Joint Convolutional Analysis and
Synthesis Sparse Representation for Single Image Layer Separation," 2017 International Conference on Computer
Vision (ICCV 2017). (paper, supp) (code) |
[110] W.
Xie, M. Wang, X. Qi, L. Zhang, "3D Surface Detail Enhancement from A
Single Normal Map," 2017
International Conference on Computer Vision (ICCV 2017). (paper) |
ACM
MM 2017
[111] L.
Yang, R. Liu, D. Zhang, L. Zhang, "Deep Location-Specific
Tracking," ACM Multimedia 2017 (MM
2017). (paper) (code) |
CVPR
2017
[112] K. Zhang, W. Zuo, S. Gu,
L. Zhang, "Learning Deep CNN Denoiser Prior for Image Restoration,"
2017 IEEE Conference on Computer Vision
and Pattern Recognition (CVPR 2017). (paper) (code) |
[113] S. Gu, W. Zuo, S. Guo,
Y. Chen, C. Chen, L. Zhang, "Learning Dynamic Guidance for Depth Image Enhancement," 2017 IEEE
Conference on Computer Vision and Pattern Recognition (CVPR 2017). (paper) (code) |
[114] P. Li, Q. Wang, L.
Zhang, "G2DeNet: Global Gaussian Distribution Embedding
Network and Its Application to Visual Recognition," 2017 IEEE Conference on Computer Vision and Pattern Recognition
(CVPR 2017). (Oral) (paper) (code) |
ICME
2017
[115] R. Tan, K. Zhang, W.
Zuo, L. Zhang, "Color Image
Demosaicking via Deep Residual Learning,"
2017 International Conference on
Multimedia and Expo (ICME 2017). (paper) (dataset&code) |
[116] L. Zhu, L. Yang, D.
Zhang, L. Zhang, "Learning A Real-time Generic Tracker using
Convolutional Neural Networks," 2017
International Conference on Multimedia and Expo (ICME 2017). (paper) (code) |
CVPR
2016
[117] S. Cai, L. Zhang, W. Zuo
and X. Feng, "A Probabilistic Collaborative Representation based
Approach for Pattern Classification," 2016 IEEE Conference on Computer Vision and Pattern Recognition
(CVPR 2016). (paper) (code) (Finally, we explained how CRC/SRC works!) |
[118] K. Ma, Q. Wu, Z. Wang, Z.
Duanmu, H. Yong, H. Li and L. Zhang, "Group MAD Competition - A New
Methodology to Compare Objective Image Quality Models," 2016 IEEE Conference on Computer Vision
and Pattern Recognition (CVPR 2016). (paper) (code&website) (IQA is far from solved yet!) |
[119] K. Wang, L. Lin, W. Zuo,
S. Gu and L. Zhang, "Dictionary Pair Classifier Driven Convolutional
Neural Networks for Object Detection," 2016 IEEE Conference on Computer Vision and Pattern Recognition
(CVPR 2016). (paper) (code) (Train stronger CNN features with
representation based classifiers!) |
[120] J. Ning, J. Yang, S.
Jiang, L. Zhang and M-H Yang, "Visual Tracking via Dual Linear
Structured SVM and Explicit Feature Map," 2016 IEEE Conference on Computer Vision and Pattern Recognition
(CVPR 2016). (paper) (code) (website) (A tracker with both high accuracy and high speed!) |
[121] F. Wang, W. Zuo, L. Lin,
D. Zhang and L. Zhang, "Joint Learning of Single-image and Cross-image Representations
for Person Re-identification," 2016
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016). (paper, sup) (code) |
[122] Q. Wang, P. Li, W. Zuo
and L. Zhang, "RAID-G: Robust Estimation of Approximate Infinite
Dimensional Gaussian with Application to Material Recognition," 2016 IEEE Conference on Computer Vision
and Pattern Recognition (CVPR 2016). (paper, sup) (code) |
[123] Q. Xie, Q. Zhao, D.
Meng, Z. Xu, S. Gu, W. Zuo and L. Zhang, "Multispectral Images Denoising
by Intrinsic Tensor Sparsity Regularization," 2016 IEEE Conference on Computer Vision and Pattern Recognition
(CVPR 2016). (paper, sup) (code) |
ICCV
2015
[124] J. Xu, L. Zhang, W. Zuo, D. Zhang, and X. Feng,
"Patch Group Based Nonlocal Self-Similarity Prior Learning for Image
Denoising," in ICCV 2015. (paper, sup) (code) (From "patch" based learning to "patch
group" based learning!) |
[125] S. Gu, W. Zuo, Q. Xie, D. Meng, X. Feng, L. Zhang,
"Convolutional Sparse Coding for Image Super-resolution," in ICCV
2015. (paper, sup) (code) (State-of-the-art super-resolution result!) |
[126] F. Chen, L. Zhang, and H. Yu,
"External Patch Prior Guided Internal Clustering for Image
Denoising," ICCV 2015. (paper, sup) (code) (Exploit external and internal information jointly
for high performance denoising!) |
CVPR
2015
[127] W. Zuo, D. Ren, S. Gu, L. Lin, and L.
Zhang, "Discriminative Learning of Iteration-wise Priors for Blind
Deconvolution," in CVPR 2015. (paper, sup) (A highly effective blind image deblurring
algorithm!) |
NIPS
2014
[128] S. Gu, L. Zhang, W. Zuo, and X. Feng,
"Projective Dictionary Pair Learning for Pattern Classification,"
In NIPS 2014. (paper, sup) (code) (From "dictionary learning" to
"dictionary pair learning"!) |
ACCV
2014
[129] P. Zhu, M. Yang, L. Zhang, and Il-Yong
Lee, "Local Generic Representation for Face Recognition with Single
Sample per Person," In ACCV 2014. (paper) (code) |
ECCV
2014
[130] K. Zhang, L. Zhang, Q. Liu, D. Zhang, and
M-H. Yang, "Fast Tracking via
Dense Spatio-Temporal Context Learning," In ECCV 2014. (paper) (code and website) |
[131] S. Cai, W. Zuo, L. Zhang, X. Feng, and P.
Wang, "Support Vector Guided Dictionary Learning," In ECCV 2014. (paper, sup) (code) |
[132] Q. Wang, W. Zuo, L. Zhang, and P. Li,
"Shrinkage Expansion Adaptive Metric Learning," In ECCV 2014. (paper, sup) (code) |
CVPR
2014
[133] S. Gu, L. Zhang, W. Zuo, and X. Feng, "Weighted Nuclear Norm Minimization with Application
to Image Denoising," In
CVPR 2014. (paper) (sup) (code) (Excellent denoising results
in terms of both PSNR and visual quality!) Q. Xie, D.
Meng, S. Gu, L. Zhang, W. Zuo, X. Feng and Z. Xu, "On the Optimal
Solution of Weighted Nuclear Norm Minimization" Technical Report, arXiv:
1405.6012. (report) (In this
technical report, we give a more complete analysis of the optimal solution of
WNNM.) |
[134] W. Lian and L. Zhang, "Point Matching in the Presence of Outliers in Both
Point Sets: A Concave Optimization Approach," In CVPR 2014. (paper) (sup) (code will be available soon) |
ICML
2014
[135] Q. Zhao, D. Meng, Z. Xu, W. Zuo, and L.
Zhang, "Robust principal component analysis with complex noise," In
ICML 2014. (paper) (code) |
ICCV
2013
[136] W. Xue, X. Mou, L. Zhang, and X. Feng,
"Perceptual Fidelity Aware Mean Squared Error," In ICCV 2013. (paper) (code) (We proved, both empirically and theoretically,
that the MSE of the smoothed images can work very well for FR-IQA!) |
[137] W. Zuo, D. Meng, L. Zhang, X. Feng, and
D. Zhang, "A Generalized Iterated Shrinkage Algorithm for Non-convex
Sparse Coding," In ICCV 2013. (paper, sup) (code) (The corrected solution of non-convex sparse coding
by iterated thresholding!) |
[138] P. Zhu, L. Zhang, W. Zuo, and D. Zhang,
"From Point to Set: Extend the Learning of Distance Metrics," In
ICCV 2013. (paper) (code) (We extended the metric learning from
point-to-point to point-to-set and set-to-set!) |
[139] P. Li, Q. Wang, and L. Zhang, "A
Novel Earth Mover's Distance Methodology for Image Matching with Gaussian
Mixture Models," In ICCV 2013. (paper) (code) (A new framework for image classification.) |
[140] P. Li, Q. Wang, W. Zuo, and L. Zhang,
"Log-Euclidean Kernels for Sparse Representation and Dictionary
Learning," In ICCV 2013. (paper) (code) (Sparse representation and dictionary
learning in a new space.) |
[141] M. Yang, Luc Van Gool, and L. Zhang,
"Sparse Variation Dictionary Learning for Face Recognition with A Single
Training Sample Per Person," In ICCV 2013. (paper) (code) (Dictionary learning with a generic dataset for face
recognition with a single training sample.) |
CVPR
2013
[142] W. Zuo, L. Zhang, C. Song, and D. Zhang,
"Texture Enhanced Image Denoising via Gradient Histogram
Preservation," In CVPR 2013.
(paper) (code) |
[143] W. Xue, L. Zhang, and X. Mou, "Learning
without Human Scores for Blind Image Quality Assessment," In CVPR 2013.
(paper) (code) |
AAAI
2013
[144] D. Meng, Z. Xu, L. Zhang, and J. Zhao,
"A Cyclic Weighted Median Method for L1
Low-Rank Matrix Factorization with Missing Entries," In AAAI 2013. (paper) (code) (A very simple but very efficient and effective L1
matrix factorization algorithm.) |
ACCV
2012
[145] S. Wang, L. Zhang, and Y. Liang, "Nonlocal
Spectral Prior Model for Low-level Vision," In ACCV12. (paper) (code will be available soon) |
ECCV
2012
[146] K. Zhang, L. Zhang, and M.H. Yang,
"Real-time Compressive Tracking," In ECCV 2012. (paper) (code and website)
(No training, no feature selection, speed up-to
40fps under Matlab, but with state-of-the-art tracking performance in terms
of both success rate and center location error!) |
[147] B. Peng and L. Zhang, "Evaluation of
Image Segmentation Quality by Adaptive Ground Truth Composition," In
ECCV 2012. (paper) (code and website)
(A novel metric to evaluate the quality of image
segmentation!) |
[148] W. Lian and L. Zhang, "Robust Point
Matching Revisited: A Concave Optimization Approach," In ECCV 2012. (paper) (code) |
[149] M.
Yang, L. Zhang, and D. Zhang, "Efficient Misalignment-Robust Representation for Real-Time Face
Recognition," In ECCV 2012. (paper) (code) |
[150] P.
Zhu, L. Zhang, Q. Hu, and Simon C.K. Shiu, "Multi-scale Patch based Collaborative Representation
for Face Recognition with Margin Distribution Optimization," In ECCV
2012. (paper) (code) |
CVPR
2012
[151] M. Yang, L. Zhang, D. Zhang, and S. Wang,
"Relaxed Collaborative
Representation for Pattern Classification," In CVPR 2012. (paper) (code) |
[152] S. Wang, L. Zhang, Y. Liang, and Q. Pan,
"Semi-Coupled Dictionary Learning with Applications to Image
Super-Resolution and Photo-Sketch Image Synthesis," In CVPR 2012. (paper) (code and website) |
ICCV
2011
[153] L. Zhang, M. Yang, and X. Feng,
"Sparse Representation or Collaborative Representation: Which Helps Face
Recognition?" In ICCV 2011. (paper,
code) |
[154] M.
Yang, L. Zhang, X. Feng, and D. Zhang, "Fisher Discrimination Dictionary Learning for Sparse
Representation," In ICCV 2011.
(paper, code) |
[155] L.
Zhang, P. Zhu, Q. Hu, and D. Zhang, "A Linear Subspace Learning Approach via Sparse Coding," In ICCV 2011. (paper,
code) |
[156] W. Dong,
L. Zhang, and G. Shi, "Centralized
Sparse Representation for Image Restoration," In ICCV 2011. (paper,
code) |
CVPR
2011
[157] Meng Yang, Lei Zhang, Jian Yang, and
David Zhang, "Robust Sparse Coding for Face Recognition," In CVPR
2011. (paper) (code) |
[158] Weisheng Dong, Xin Li, Lei Zhang, and
Guangming Shi, "Sparsity-based Image Denoising via Dictionary Learning
and Structural Clustering," In CVPR 2011 (oral). (paper)
(code) |
ECCV
2010
[159] M. Yang
and L. Zhang, "Gabor Feature based
Sparse Representation for Face Recognition with Gabor Occlusion Dictionary,"
In ECCV 2010. (code) |
[160] W. Lian
and L. Zhang, "Rotation invariant
non-rigid shape matching in cluttered scenes," In ECCV 2010. (code) |
CVPR
2008-2010
[161] W. Li, L.
Zhang, D. Zhang, G. Lu, and J. Yan, "Efficient Joint
2D and 3D Palmprint Matching with Alignment Refinement,"
In CVPR 2010. (database) |
[162] Q. Zhao, L. Zhang, D. Zhang, W. Huang, and J. Bai,
"Curvature
and Singularity Driven Diffusion for Oriented Pattern Enhancement with
Singular Points," In CVPR09. |
[163] L. Zhang, Q. Gao, and D. Zhang, "Directional Independent
Component Analysis with Tensor Representation," In
CVPR2008, pp.1-7, 23-28, June, Anchorage, Alaska, U.S. (Oral). |
Other Conference Papers
[164] Lin Zhang,
Lei Zhang, X. Mou, and D. Zhang, "A Comprehensive Evaluation of Full Reference Image
Quality Assessment Algorithms," In ICIP 2012. (paper) |
[165] W. Dong, G. Shi, L. Zhang, and X. Wu, "Super-resolution with nonlocal regularized
sparse representation," In SPIE VCIP 2010. (Best paper award) |
[166] Meng Yang, Lei Zhang, Daivd Zhang, and Jian Yang,
"Metaface Learning for Sparse
Representation based Face Recognition," In ICIP 2010. (code) |
[167] Lin Zhang, Lei Zhang, Zhenhua Guo, and David Zhang,
"MONOGENIC-LBP: A NEW APPROACH FOR
ROTATION INVARIANT TEXTURE CLASSIFICATION," In ICIP 2010.
(code) |
[168] Lin Zhang, Lei Zhang, and X. Mou, "RFSIM: A
Feature based Image Quality Assessment Metric using Riesz Transforms,"
In ICIP 2010. (code) |
[169] Kaihua Zhang, Lei Zhang, and Su Zhang, "A
Variational Multiphase Level Set Approach to Simultaneous Segmentation and
Bias Correction," In ICIP 2010. (code) |
[170] Qijun Zhao, Feng Liu, Lei Zhang, and David Zhang,
"A comparative study on
quality assessment of high resolution fingerprint images,"
In ICIP 2010. |
[171] Jin Xie, Lei Zhang, Jane You, and David Zhang,
"TEXTURE CLASSIFICATION VIA
PATCH-BASED SPARSE TEXTON LEARNING," In ICIP 2010. |
[172] Meng Yang, Lei Zhang, Lin Zhang, and David Zhang,
"Monogenic Binary
Pattern (MBP): A Novel Feature Extraction and Representation Model for Face
Recognition," In ICPR 2010. |
[173] Lei Zhang, Meng Yang, Zhizhao Feng, and David
Zhang, "On the Dimensionality Reduction for Sparse Representation based
Face Recognition," In ICPR 2010. (paper) (code) |
[174] Qijun Zhao, Feng Liu, Lei Zhang, and David Zhang,
"Parallel versus Hierarchical
Fusion of Extended Fingerprint Features," In ICPR 2010. |
[175] Feng Liu, Qijun Zhao, Lei Zhang, and David Zhang,
"Fingerprint
Pore Matching based on Sparse Representation," In ICPR
2010. |
[176] Bob Zhang, Lei Zhang,
Jane You, and Fakhri Karray, "Microaneurysm (MA) Detection via Sparse
Representation Classifier with MA and Non-MA Dictionary Learning," In ICPR 2010. (paper) |
[177] B. Peng,
L. Zhang, and J. Yang, "Iterated Graph Cuts for Image
Segmentation," In ACCV 2009. (software) |
[178] Lin Zhang,
Lei Zhang, and D. Zhang, "A Multi-Scale Bilateral
Structure Tensor Based Corner Detector," In ACCV
2009. (code) |
[179] Weisheng Dong, Lei Zhang, Guangming Shi, and Xiaolin
Wu, "Nonlocal
back-projection for adaptive image enlargement," In ICIP
2009. (code) |
[180] Lin Zhang, Lei Zhang, and David Zhang, "Finger-Knuckle-Print: A
New Biometric Identifier," In ICIP 2009. |
[181] Lin Zhang, Lei
Zhang, and David Zhang, "Finger-Knuckle-Print
Verification Based On Band-Limited Phase-Only Correlation," The 13th International Conference on
Computer Analysis of Images and Patterns (CAIP09). |
[182] Q. Zhao, L.
Zhang, D. Zhang, and N. Luo, "Direct Pore Matching for
Fingerprint Recognition,"
International Conference on Biometrics 2009 (ICB09), pp. 597-606, Alghero, Italy, June 2-5, 2009. |
[183] Wei Li, Lei
Zhang, and David Zhang, "Three Dimensional Palmprint Recognition," 2009 IEEE International Conference on Systems,
Man, and Cybernetics, SMC09. |
[184] X. Li, B.
Gunturk, and L. Zhang, "Image demosaicing: a
systematic survey," Visual Communications and Image
Processing 2008, Proceedings of the
SPIE, Volume 6822, pp. 68221J-68221J-15 (2008). San Jose, CA, USA |
[185] Q. Zhao, L.
Zhang, D. Zhang, and N. Luo, "Adaptive Pore Model for
Fingerprint Pore Extraction,"
Proceedings of International Conference on Pattern Recognition 2008 (ICPR08),
pp. 1-4, Tampa, Florida, USA, Dec. 8-11, 2008. |
[186] D. Zhang, G. Lu,
W. Li, L. Zhang, and N. Luo, "Three Dimensional Palmprint Recognition using
Structured Light Imaging," 2nd
IEEE International Conference on Biometrics: Theory, Applications and Systems
(BTAS08), Sept. 29-Oct. 1
2008, pp. 1-6. Hyatt Regency Crystal City, U.S. |
[187] Lei Zhang, Zhenhua Guo, Zhou Wang, and
David Zhang, "Palmprint verification using complex wavelet
transform," In
ICIP07, September 16-19, 2007, San Antonio, Texas, USA. Volume
2, Page(s): II - 417 - II - 420. |
[188] Marko Slyz and Lei Zhang, "A Block-based Inter-band Lossless Hyperspectral
Image Compressor," DCC05 (Data Compression Conference) 2005,
pp.427-436, Cliff Lodge, USA, 29-31 March 2005. |
Journal Papers
Image
Restoration and Enhancement
[189] L. Sun, J. Liang, S. Liu, H. Yong, L. Zhang, "Perception-Distortion
Balanced Super-Resolution: A Multi-Objective Optimization Perspective," IEEE
Trans. on Image Processing, 2024. (paper) (code) |
[190] Z. Zhang, R. Li, S. Guo, Y. Cao, L. Zhang,
"TMP: Temporal Motion Propagation for Online Video
Super-Resolution," IEEE Trans. on Image Processing, 2024. (paper) (code) |
[191] Z.
Yue, H. Yong, Q. Zhao, L. Zhang, D. Meng, and Kwan-Yee K. Wong, "Deep
Variational Network Toward Blind Image Restoration," IEEE Trans. on
Pattern Analysis and Machine Intelligence, 2024. (paper) (code) |
[192] X.
Li, S. Zhang, S. Zhou, L. Zhang, W. Zuo, "Learning Dual Memory
Dictionaries for Blind Face Restoration," IEEE Trans. on Pattern
Analysis and Machine Intelligence, 2022. (paper) (code) |
[193] J.
Ma, S. Guo, L. Zhang, "Text Prior Guided Scene Text Image
Super-Resolution," IEEE Trans. on Image
Processing. (paper) (code) (Text
images can be much better enhanced than what you think.) |
[194] S. Guo, Z. Liang, L.
Zhang, "Joint Denoising and Demosaicking with Green Channel Prior for
Real-world Burst Images," IEEE
Trans. on Image Processing, vol. 30, pp. 6930-6942, Aug. 2021. (paper) (code) |
[195] K.
Zhang, Y. Li, W. Zuo, L. Zhang, Luc Van Gool, Radu Timofte,
"Plug-and-Play Image Restoration with Deep Denoiser Prior," IEEE Trans. on Pattern Analysis and
Machine Intelligence, 2021. (paper) (code) |
[196] Z. Liang, J. Cai, Z. Cao,
L. Zhang, "CameraNet: A Two-Stage Framework for Effective Camera ISP
Learning," IEEE Trans. on Image
Processing. (paper) (code) |
[197] M. Li, X. Cao, Q. Zhao, L.
Zhang, D. Meng, "Online Rain/Snow Removal from Surveillance
Videos," IEEE Trans. on Image
Processing. (paper) (code) |
[198] H. Zeng, J. Cai, L. Li, Z.
Cao, L. Zhang, "Learning Image-adaptive 3D Lookup Tables for High
Performance Photo Enhancement in Real-time," IEEE Trans. on Pattern Analysis and Machine Intelligence. (paper) (supp) (code) (High quality adaptive photo enhancement in
real-time (<2ms for 4K resolution images)!) |
[199] X. Li, G. Hu, J. Zhu, W.
Zuo, M. Wang, L. Zhang, "Learning Symmetry Consistent Deep CNNs for Face
Completion," IEEE Trans. on Image
Processing, vol. 29, issue 7, pp. 7641-7655, July 2020. (paper) (code) |
[200] Z. Li, W. Zuo, Z. Wang, L.
Zhang, "Confidence-based Large-scale Dense Multi-view Stereo," IEEE Trans. on Image Processing, vol.
29, issue 6, pp. 7176-7191, June 2020. (paper) |
[201] S. Gu, S. Guo, W. Zuo, Y.
Chen, R. Timofte, Luc Van Gool, L. Zhang, "Learned Dynamic Guidance for
Depth Image Reconstruction," IEEE
Trans. on Pattern Analysis and Machine Intelligence. (paper) (code) |
[202] J. Cai, W. Zuo, L. Zhang,
"Dark and Bright Channel Prior Embedded Network for Dynamic Scene
Deblurring," IEEE Trans. on Image
Processing. (paper) (code) |
[203] H. Li, K. Ma, H. Yong, L.
Zhang, "Fast Multi-Scale Structural Patch Decomposition for
Multi-Exposure Image Fusion," IEEE
Trans. on Image Processing. (paper) (code) |
[204] J. Cai, Z. Cao, L. Zhang,
"Learning a Single Tucker Decomposition Network for Lossy Image
Compression with Multiple Bits-Per-Pixel Rates," IEEE Trans. on Image Processing. (paper) (code) |
[205] D. Ren, W. Zuo, D. Zhang, L. Zhang, M-H. Yang,
"Simultaneous Fidelity and Regularization Learning for Image
Restoration," to appear, IEEE
Trans. on Pattern Analysis and Machine Intelligence. (paper) (code) |
[206] R. Liu, X. Fan, M. Hou, Z.
Jiang, Z. Luo, L. Zhang, "Learning Aggregated Transmission Propagation
Networks for Haze Removal and Beyond," IEEE Transactions on Neural Networks and Learning Systems, vol. 30, issue 10, pp. 2973-2986, Oct. 2019. (paper) |
[207] R. Liu, L. Ma, Y. Wang, L.
Zhang, "Learning Converged Propagations with Deep Prior Ensemble for
Image Enhancement," IEEE Trans. on
Image Processing, vol. 28, issue 3, pp. 1528-1543, Mar. 2019. (paper) (code) |
[208] F. Zhu, Z. Liang, X. Jia,
L. Zhang, Y. Yu, "A Benchmark for Edge-Preserving Image Smoothing," IEEE Trans. on Image Processing,
2019. (paper) (code&dataset) |
[209] H. Yong, J. Huang, W. Xiang, X. Hua, L. Zhang, "Panoramic
Background Image Generation for PTZ Cameras," IEEE Trans. on Image Processing, 2019. (paper) (code) |
[210] K. Zhang, W. Zuo, L. Zhang, "FFDNet: Toward a Fast and
Flexible Solution for CNN based Image Denoising," IEEE Trans.
on Image Processing, vol. 27, issue
9, pp. 4608-4622, Sept. 2018. (paper) (code) (Fast, flexible yet effective
denoising!) |
[211] J. Xu, L. Zhang, D. Zhang,
"External Prior Guided Internal Prior Learning for Real-World Noisy
Image Denoising," IEEE Trans. on
Image Processing, vol. 27, issue 6, pp. 2996-3010, June 2018. (paper, supp) (code) |
[212] D.W. Ren, W.M. Zuo, D.
Zhang, J. Xu, L. Zhang, "Partial Deconvolution with Inaccurate Blur
Kernel," IEEE Trans. on Image
Processing, vol. 27, issue 1, pp. 511-524, Jan. 2018. |
[213] J. Cai, S. Gu, L. Zhang, "Learning a Deep
Single Image Contrast Enhancer from Multi-Exposure Images," IEEE Trans. on Image Processing, vol.
27, issue 4, pp. 2049-2062, April 2018. (paper) (dataset&code) |
[214] H. Li, X. Jia, L. Zhang, "Clustering based
Content and Color Adaptive Tone Mapping," Computer Vision and Image Understanding, vol. 168, pp. 37-49,
Mar. 2018. (paper) (code) |
[215] L. Zhang and W. Zuo, "Image Restoration: From
Sparse and Low-rank Priors to Deep Priors," IEEE Signal Processing Magazine, vol. 34, issue 5, pp. 172-179,
Sept. 2017. (lecture-notes article, paper, slides) |
[216] K. Zhang, W. Zuo, Y. Chen, D. Meng, L. Zhang, "Beyond a
Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising," IEEE Trans. on Image Processing, issue 7, pp. 3142-3155,
July 2017. (paper) (code) |
[217] K. Ma, H. Li, H. Yong, Z. Wang, D. Meng, L. Zhang,
"Robust
Multi-Exposure Image Fusion: A Structural Patch Decomposition Approach,"
IEEE Trans. on Image Processing, vol. 26,
issue 5, pp. 2519 - 2532, May 2017. (paper) (sup) (code) |
[218] J. Jiao, Q. Yang, S. He, S. Gu, L. Zhang, R.W.H.
Lau, "Joint Image Denoising and Disparity Estimation via Stereo
Structure PCA and Noise-tolerant Cost," International Journal of Computer Vision, vol. 124, issue 2, pp. 204-222, Sept. 2017. (paper) (code) |
[219] S. Gu, Q. Xie, D. Meng, W. Zuo, X. Feng, L. Zhang,
"Weighted Nuclear Norm Minimization and Its Applications to Low Level
Vision," International
Journal of Computer Vision, vol. 121, issue 2, pp. 183-208, Jan. 2017. (paper) (code_Denoising,
code_RPCA,
code_MC) |
[220] Y. Xie, S. Gu, Y. Liu, W. Zuo, W. Zhang, L. Zhang,
"Weighted Schatten p-Norm Minimization for Image Denoising and
Background Subtraction," IEEE Trans. on Image Processing, vol. 25, issue 10,
pp. 4842 - 4857, Oct. 2016. (paper) (code) |
[221] W. Zuo, D. Ren, D. Zhang, S. Gu, L.
Zhang, "Learning Iteration-wise Generalized Shrinkage-Thresholding
Operators for Blind Deconvolution," IEEE
Trans. on Image Processing, vol. 25, issue 4, pp. 1751-1764, April 2016.
(paper) (code) |
[222] Z. Li, K. Wang, W. Zuo, D. Meng, L. Zhang,
"Detail-preserving and Content-aware Variational Multi-view Stereo
Reconstruction," IEEE Trans. on
Image Processing, vol. 25, issue 2, pp. 864-877, Feb. 2016. (paper) |
[223] W. Zuo, L. Zhang, C. Song, D. Zhang, and H. Gao,
"Gradient Histogram Estimation and Preservation for Texture Enhanced
Image Denoising," IEEE Trans. on
Image Processing, vol. 23, issue 6, pp. 2459-2472, June 2014. (paper) (code) (This is an extension of our GHP
work in CVPR'13) |
[224] J. Jiang, L. Zhang, and J. Yang, "Mixed Noise Removal by Weighted Encoding
with Sparse Nonlocal Regularization," IEEE Trans. on Image Processing, vol. 23, issue 6, pp. 2651-2662,
June 2014. (paper) (sup) (code) |
[225] W. Dong, L. Zhang, G. Shi, and X. Li,
"Nonlocally Centralized Sparse Representation for Image
Restoration," IEEE Trans. on Image
Processing, vol. 22, no. 4, pp. 1620-1630, Apr. 2013. (paper) (website) (code) (This paper is an
improvement of our ICCV11 paper "Centralized
Sparse Representation for Image Restoration".) |
[226] W. Dong, L. Zhang, R. Lukac, and G. Shi,
"Sparse Representation based Image Interpolation with Nonlocal
Autoregressive Modeling," IEEE
Trans. on Image Processing, vol. 22,
no. 4, pp. 1382-1394, Apr. 2013. (paper) (website) (code) |
[227] W. Dong, L. Zhang, G. Shi, and X. Wu, "Image
deblurring and super-resolution by adaptive sparse domain selection and
adaptive regularization," IEEE
Trans. on Image Processing, vol. 20, no. 7, pp. 1838-1857, July 2011. (paper,
matlab code & website) |
[228] L. Zhang, W. Dong, D. Zhang, and G. Shi,
"Two-stage Image Denoising by Principal Component Analysis with Local
Pixel Grouping," Pattern Recognition, vol. 43, issue 4, pp.
1531-1549, April 2010. (paper, matlab code, website) (Code
optimized!) |
[229] L. Zhang and X.
Wu, "An edge-guided image
interpolation algorithm via directional filtering and data fusion," IEEE
Trans. on Image Processing, vol.
15, pp. 2226-2238, Aug. 2006. (paper, matlab code) |
[230] L. Zhang, X. Wu, A. Buades, and X. Li, "Color
Demosaicking by Local Directional Interpolation and Non-local Adaptive
Thresholding," Journal of
Electronic Imaging 20(2), 023016 (Apr-Jun 2011), DOI:10.1117/1.3600632. (paper,
website and dataset, code) |
[231] L. Zhang, W. Dong, X. Wu, and G. Shi, "Spatial-Temporal
Color Video Reconstruction from Noisy CFA Sequence," IEEE Trans. on Circuits
and Systems for Video Technology,
vol. 20, no. 6, pp. 838-847, June 2010. (paper) |
[232] L. Zhang, R.
Lukac, X. Wu, and D. Zhang, "PCA-based
Spatially Adaptive Denoising of CFA Images for Single-Sensor Digital
Cameras," IEEE Trans. on Image Processing,
vol. 18, no. 4, pp. 797-812, April 2009. (paper, matlab code,
website) |
[233] L. Zhang, X. Wu,
and D. Zhang, "Color Reproduction from Noisy CFA Data of Single Sensor
Digital Cameras," IEEE Trans. Image Processing, vol. 16, no.
9, pp. 2184-2197, Sept. 2007. (paper, matlab code, website) |
[234] L. Zhang, X. Li, and D. Zhang, "Image Denoising and Zooming under the LMMSE
Framework," IET Image Processing, Vol. 6,
Issue 3, pp. 273-283, 2012. (paper) (code) |
[235] L. Zhang and X.
Wu, "Color demosaicking via
directional linear minimum mean square-error estimation," IEEE Trans.
on Image Processing, vol. 14,
pp. 2167-2178, Dec. 2005. (paper, matlab code) |
[236] F. Zhang, X. Wu, X. Yang, W. Zhang, and L.
Zhang,
"Robust Color Demosaicking with
Adaptation to Varying Spectral Correlations," IEEE Trans. on Image
Processing, vol. 18, no. 12, pp. 2706-2717, Dec 2009. (paper) |
[237] X. Wu and L. Zhang,
"Improvement of color video
demosaicking in temporal domain," IEEE
Trans. on Image Processing, vol. 15, pp. 3138-3151, Oct. 2006. (paper, software) |
[238] X. Wu and L. Zhang, "Temporal color video demosaicking via motion
estimation and data fusion," IEEE Trans.
on Circuits and Systems for Video Technology, vol. 16, pp. 231-240, Feb.
2006. (paper) |
[239] L. Zhang, B. Paul, and X.
Wu, "Multiscale LMMSE-based image denoising with optimal wavelet
selection," IEEE Trans. on Circuits and Systems for Video Technology,
vol. 15, pp. 469-481, April 2005. (paper,
matlab code) |
[240] Q. Pan, L. Zhang, H. Zhang, and G. Dai, "Two
de-noising methods by wavelet transform," IEEE Trans. on Signal
Processing, vol. 47, pp. 3401-3406, Dec. 1999. (paper) |
Image Quality
and Aesthetic Assessment
[241] H. Zeng, L. Li, Z. Cao, L.
Zhang, "Grid Anchor based Image Cropping: A New Benchmark and An
Efficient Model," IEEE Trans. on
Pattern Analysis and Machine Intelligence. (paper) (code) (Extension of our CVPR19 work with a much
bigger dataset.) |
[242] H. Zeng, Z. Cao, L. Zhang,
A.C. Bovik, "A Unified Probabilistic Formulation of Image Aesthetic
Assessment," IEEE Trans. on Image
Processing. (paper) (code) |
[243] K. Ma, Z. Duanmu, Z. Wang, Q. Wu, W. Liu, H. Yong, H. Li, L.
Zhang, "Group Maximum Differentiation Competition: Model Comparison with
Few Samples," to appear, IEEE
Trans. on Pattern Analysis and Machine Intelligence. (paper) (code) |
[244] J. Kim, H. Zeng, D. Ghadiyaram, S. Lee, L. Zhang,
A.C. Bovik, "Deep Convolutional Neural Models for Picture Quality
Prediction," IEEE Signal
Processing Magazine, vol. 34, issue 6, pp. 130-141, Nov. 2017. (paper) |
[245] K. Ma, Z. Duanmu, Q. Wu, Z. Wang, H. Yong, H. Li, L. Zhang,
"Waterloo Exploration Database: New Challenges for Image Quality
Assessment Models," IEEE Trans. on Image Processing,
vol.
26, issue 2, pp. 1004 - 1016, Feb.
2017. (paper) (code&database) |
[246] Lin Zhang, Lei Zhang, and Alan C. Bovik, "A
Feature-Enriched Completely Blind Image Quality Evaluator," IEEE Trans.
on Image Processing, vol. 24, issue
8, pp. 2579 - 2591, Aug. 2015. (paper) (code and website) (An
"opinion-unaware" method which outperforms all
"opinion-aware" methods!) |
[247] W. Xue, X. Mou, L. Zhang, A. Bovik, and X. Feng,
"Blind Image Quality Assessment Using Joint Statistics of Gradient
Magnitude and Laplacian Features," IEEE
Trans. on Image Processing, vol. 23, issue 11, pp. 4850 - 4862, Nov.
2014. (paper) (code) |
[248] W. Xue, L. Zhang, X. Mou, and A. C. Bovik, "Gradient
Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality
Index," IEEE Transactions on Image Processing, vol. 23, issue 2, pp. 684
- 695, Feb., 2014. (paper) (code) (website) (A very simple but highly efficient and
effective full reference IQA algorithm!) |
[249] Lin Zhang, Lei Zhang, X. Mou, and D. Zhang,
"FSIM: A Feature Similarity Index for Image Quality Assessment," IEEE Trans. Image Processing, vol. 20, no. 8, pp. 2378-2386, 2011. (paper, website & code) |
[250] M. Zhang, X. Mou, and L. Zhang, "Non-Shift Edge
based Ratio (NSER): An Image Quality Assessment Metric Based on Early Vision
Features," IEEE Signal Processing
Letters, vol. 18, no. 5, pp. 315-318, May, 2011. (paper) |
Pattern
Recognition, Object Detection, Machine Learning
[251] L. Li, J. Xie, P. Li, and
L. Zhang, "Detachable Second-order Pooling: Towards High Performance
First-order Networks," IEEE
Transactions on Neural Networks and Learning Systems. (paper) (code) |
[252] Y. Zhang, B. Deng, H.
Tang, L. Zhang, K. Jia, "Unsupervised Multi-Class Domain Adaptation:
Theory, Algorithms, and Practice," IEEE
Trans. on Pattern Analysis and Machine Intelligence. (paper) (code) |
[253] X. Jia, X. Feng, W. Wang,
L. Zhang, "Generalized Unitarily Invariant Gauge Regularization for Fast
Low-Rank Matrix Recovery," IEEE
Transactions on Neural Networks and Learning Systems. (paper) (code) |
[254] Q. Wang, J. Xie, W. Zuo,
L. Zhang, P. Li, "Deep CNNs Meet Global Covariance Pooling: Better
Representation and Generalization," IEEE
Trans. on Pattern Analysis and Machine Intelligence. (paper) |
[255] Z. Yue, H. Yong, D. Meng, Q. Zhao, Y. Leung, L. Zhang,
"Robust Multi-view Subspace Learning with Non-independently and
Non-identically Distributed Complex Noise," IEEE Transactions on Neural Networks and Learning Systems. (paper) (code) |
[256] W. An, H. Wang, Q. Sun, J.
Xu, Y. Luo, L. Zhang, "PID Controller based Stochastic Optimization
Acceleration for Deep Neural Networks," IEEE Transactions on Neural Networks and Learning Systems. DOI: 10.1109/TNNLS.2019.2963066 |
[257] K. Wang, L. Lin, X. Yan, Z. Chen, D. Zhang, L. Zhang,
"Cost-Effective Object Detection: Active Sample Mining with Switchable
Selection Criteria", IEEE
Transactions on Neural Networks and Learning Systems, vol. 30, issue 3,
pp. 834-850, Mar. 2019. (paper) |
[258] Z. Fu, Y. Chen, H. Yong, R. Jiang, L. Zhang, X. Hua,
"Foreground Gating and Background Refining Network for Surveillance
Object Detection," IEEE Trans. on
Image Processing, 2019. (paper) (code) |
[259] L. Lin, K. Wang, D. Meng, W. Zuo, L. Zhang, "Active
Self-Paced Learning for Cost-Effective and Progressive Face
Identification," IEEE Trans. on Pattern Analysis and Machine
Intelligence, vol. 40, issue 1, pp. 7-19, 2018. (paper) (code) |
[260] W. Zuo. F. Wang, D. Zhang,
L. Lin, Y. Huang, D. Meng, L. Zhang, "Distance Metric Learning via
Iterated Support Vector Machines for Person Verification," IEEE Trans. on Image Processing, vol.
26, issue 10, pp. 4937-4950, Oct. 2017. (paper) (code) |
[261] P. Li, H. Zeng, Q. Wang, Simon C. K. Shiu, L. Zhang,
"High-order Local Pooling and Encoding Gaussians over a Dictionary
of Gaussians," IEEE
Trans. on Image Processing, vol. 26, issue 7, pp. 3372-3384, July
2017. (paper) (code) |
[262] L. Lin, G. Wang, W. Zuo, X. Feng, and L. Zhang,
"Cross-Domain Visual Matching via Generalized Similarity Measure and
Feature Learning," IEEE Trans. on
Pattern Analysis and Machine Intelligence, vol. 39, issue 6, pp. 1089-1102, June 2017. (paper) (code) |
[263] P. Li, Q. Wang, H. Zeng, L. Zhang, "Local
Log-Euclidean Multivariate Gaussian Descriptor and Its Application to Image
Classification," IEEE Trans. on Pattern Analysis and Machine
Intelligence, vol. 39, issue 4, pp. 803-817, April 2017. (paper) (code) |
[264] Q.
Wang, P. Li, L. Zhang, W. Zuo, "Towards Effective Codebookless Model for
Image Classification," Pattern
Recognition, vol. 59, pp. 63-71, Nov. 2016. (paper) (code) |
[265] L.
Lin, K. Wang, W. Zuo, M. Wang, J. Luo, and L. Zhang, "A Deep Structured
Model with Radius-Margin Bound for 3D Human Activity Recognition," International Journal of Computer Vision,
vol. 118, issue. 2, pp. 256-273, June. 2016. (paper, dateset&code) |
[266] F. Wang, W. Zuo, L. Zhang, Deyu Meng, and David
Zhang, "A Kernel Classification Framework for Metric Learning," IEEE Transactions on Neural Networks and
Learning Systems, vol. 26, issue 9, pp. 1950-1962, Sept. 2015. (paper) (code) (We make metric learning hundred to thousand times
faster!) |
[267] M. Yang, L. Zhang, X. Feng, and D. Zhang, "Sparse
Representation based Fisher Discrimination Dictionary Learning for Image
Classification," International
Journal of Computer Vision, vol. 109, issue 3, pp. 209-232, Sept. 2014. (paper) (code) (This is an extension of our FDDL
work in ICCV'11) |
[268] P. Zhu, W. Zuo, L. Zhang, S. Shiu, and D. Zhang,
"Image Set based Collaborative Representation for Face
Recognition," IEEE Trans. on
Information Forensics and Security, vol. 9, no. 7, pp. 1120-1132, July
2014. (paper) (code) |
[269] L. Zhang, M. Yang, X. Feng, Y. Ma, and D. Zhang,
"Collaborative Representation based Classification for Face
Recognition," Technical report. arXiv: 1204.2358. (paper) (code) (This is a
substantial extension of our ICCV11 paper "Sparse Representation or
Collaborative Representation: Which Helps Face Recognition?") |
[270] M. Yang, L. Zhang, J. Yang, and D. Zhang, "Regularized Robust Coding for Face
Recognition," IEEE
Transactions on Image Processing, Volume 22, Issue 5, Pages 1753-1766,
May 2013. (paper) (code) (This paper is a substantial
extension of our CVPR11 paper "Robust
sparse coding for face recognition".) |
[271] M. Yang, L. Zhang, S. Shiu, and D. Zhang,
"Monogenic Binary Coding: An Efficient Local Feature Extraction Approach
to Face Recognition," IEEE Trans.
on Information Forensics and Security, vol. 7, no. 6, pp. 1738-1751, Dec.
2012. (paper) (code) (In this work we
proposed a new binary coding scheme, namely MBC, which has very high
efficiency and accuracy in face representation and recognition.) |
[272] M. Yang, L. Zhang, S. Shiu, and D. Zhang,
"Robust Kernel Representation with Statistical Local Features for Face
Recognition," IEEE Transactions on
Neural Networks and Learning Systems, Volume 24, Issue 6, Pages 900-912,
June 2013. (paper) (code) |
[273] M. Yang, Z. Feng, S. Shiu, and L. Zhang, "Fast
and Robust Face Recognition via Coding Residual Map Learning based Adaptive
Masking," Pattern
Recognition, vol. 47, no. 2, pp. 535-543, Feb. 2014. (paper) (code will be available soon) |
[274] Z. Feng*, M. Yang*, L. Zhang,
Y. Liu, and D. Zhang, "Joint Discriminative Dimensionality Reduction and
Dictionary Learning for Face Recognition," Pattern Recognition, Volume 46, Issue 8, Pages 2134-2143, Aug.
2013. (*The two authors contribute equally.) (paper) (code) |
[275] M. Yang, L. Zhang, S. Shiu, and D. Zhang,
"Gabor Feature based Robust Representation and Classification for Face
Recognition with Gabor Occlusion Dictionary," Pattern Recognition,
Volume 46, Issue 7, Pages 1865-1878, July 2013. (paper) (code) |
[276] J. Yang, D. Chu, L. Zhang, Y. Xu, and J. Yang,
"Sparse Representation Classifier Steered Discriminative Projection with
Applications to Face Recognition," IEEE
Transactions on Neural Networks and Learning Systems, Volume 24, Issue 7,
Pages 1023-1035, July 2013. |
[277] J. Yang, L. Zhang, Y. Xu, and Jing-yu Yang,
"Beyond Sparsity: the Role of L1-optimizer in Pattern
Classification," Pattern
Recognition, vol. 45, issue 3, Pages 1104-1118, March 2012. |
[278] J. Yang, L. Zhang, J.
Yang, and D. Zhang, "From
Classifiers to Discriminators: A Nearest Neighbor Rule Induced Discriminant
Analysis," Pattern Recognition, vol. 44, issue 7, pp. 1387-1402, July 2011. |
[279] W. Yang, C.Y.
Sun, and L. Zhang, "A
Multi-Manifold Discriminant Analysis Method for Image Feature
Extraction,"
Pattern Recognition, vol. 44, issue 8, pp. 1649-1657, August 2011. (paper) |
[280] B. Zhang, L. Zhang, D. Zhang, and L. Shen,
"Directional Binary Code with Application to PolyU Near-Infrared Face
Database," Pattern
Recognition Letters, vol. 31, issue 14, pp. 2337-2344, Oct.
2010. (paper) (database) |
[281] W. Di, L. Zhang, D. Zhang, and Q. Pan, "Studies
on Hyperspectral Face Recognition in
Visible Spectrum with Feature Band Selection," IEEE Trans. on System,
Man and Cybernetics, Part A, vol. 40, issue 6, pp. 1354 - 1361, Nov. 2010. (paper) (database) |
[282] J. Yang, C. Liu, and L. Zhang, "Color Space Normalization: Enhancing the
Discriminating Power of Color Spaces for Face Recognition," Pattern Recognition, 2010,
43(4), 1454-1466, April 2010. (paper) |
[283] Q. Gao, L. Zhang, D.
Zhang, and H. Xu, "Independent
components extraction from image matrix," Pattern Recognition Letters, vol. 31, issue 3, pp. 171 - 178,
Feb. 2010. (paper) |
[284] Q.
Gao, L. Zhang, and D. Zhang, "Sequential Row-Column Independent
Component Analysis for Face Recognition," Neurocomputing, vol.
72, pp. 1152-1159, Jan. 2009. (paper) |
[285] Q.
Gao, L. Zhang, and D. Zhang, "Face Recognition using FLDA with Single
Training Image Per-person," Applied
Mathematics and Computation, vol. 205, pp. 726-734, 2008. (paper, code) |
[286] Y. Zhao, L.
Zhang, and S. Kong, "Band Subset Based Clustering and Fusion for Hyperspectral Imagery
Classification," IEEE Trans. on
Geoscience and Remote Sensing, vol. 49, no. 2, pp. 747-756, Feb. 2011. (paper) |
Image and Video
Segmentation
[287] W. Li, W. Liu, J. Zhu, M. Cui, R. Yu, X. Hua, L.
Zhang, "Box2Mask: Box-supervised Instance Segmentation via Level-set
Evolution," IEEE Trans. on Pattern Analysis and Machine Intelligence,
2024. (paper) (code) |
[288] W. Liu, W. Li, J. Zhu, M. Cui, X. Xie, L. Zhang,
"Improving Nighttime Driving-Scene Segmentation via Dual Image-adaptive
Learnable Filters," IEEE Trans. on Circuits and Systems for Video
Technology. (paper) (code) |
[289] Y. Yin, D. Xu, X. Wang and
L. Zhang, "Directional Deep Embedding and Appearance Learning for Fast
Video Object Segmentation," IEEE
Transactions on Neural Networks and Learning Systems. (paper) (code) |
[290] H. Yong, D. Meng, W. Zuo,
L. Zhang, "Robust Online Matrix Factorization for Dynamic Background
Subtraction," IEEE Trans. on
Pattern Analysis and Machine Intelligence, vol. 40, issue 7, pp. 1726-1740, July 2018. (paper) (code) |
[291] B. Peng, L. Zhang, X. Mou, M-H. Yang, "Evaluation of
Segmentation Quality via Adaptive Composition of Reference
Segmentations," IEEE Trans. on Pattern Analysis and Machine
Intelligence, vol. 39, issue 10, pp. 1929-1941, Oct.
2017. (paper) (code&database) |
[292] B. Peng, L. Zhang, and D. Zhang, "A Survey of Graph
Theoretical Approaches to Image Segmentation," Pattern Recognition,
Volume 46, Issue 3, Pages 1020-1038, Mar. 2013. (paper) |
[293] K. Zhang, L. Zhang, H. Song, and D. Zhang,
"Re-initialization Free Level Set Evolution via Reaction
Diffusion," IEEE Transactions on
Image Processing, Volume 22, Issue 1, Pages 258-271, Jan. 2013. (paper) (code and website) (This
work unifies the level set evolution under the reaction diffusion framework,
which is completely free of re-initialization.) |
[294] S. Li, H. Lu, and
L. Zhang, "Arbitrary body
segmentation in static images," Pattern Recognition,
Volume
45, Issue 9, Pages 3402-3413, Sept. 2012. |
[295] B. Peng, L. Zhang, and D. Zhang, "Automatic
Image Segmentation by Dynamic Region Merging," IEEE Trans. on Image Processing, vol. 12, no. 12, pp. 3592-3605,
2011. (paper, software, website) (Source code) |
[296] B. Peng, L. Zhang, D. Zhang, and J. Yang,
"Image Segmentation by Iterated Region Merging with Localized Graph
Cuts," Pattern Recognition,
vol. 44, issues 10-11, pp. 2527-2538, October-November 2011. (paper) (software) |
[297] K. Zhang, L.
Zhang, H. Song, and W. Zhou, "Active
contours with selective local or global segmentation: a new formulation and
level set method," Image and
Vision Computing, vol. 28, issue 4, pp. 668-676,
April 2010. (paper, matlab code, website) |
[298] K. Zhang, H. Song, and L. Zhang, "Active Contours Driven by Local Image Fitting
Energy," Pattern recognition, vol. 43, issue 4, pp. 1199-1206, April 2010. (paper, matlab code) |
[299] J. Ning, L.
Zhang, D. Zhang, and C. Wu, "Interactive Image Segmentation by Maximal
Similarity based Region Merging," Pattern
Recognition, vol. 43, pp. 445-456, Feb, 2010. (paper,
website & code) |
[300] Y. Zhao, L.
Zhang, D. Zhang, and Q. Pan, "Object Separation by Polarimetric and
Spectral Imagery Fusion," Computer
Vision and Image Understanding, vol.
113, no. 8, pp. 855-866, Aug. 2009. (paper, dataset) |
Object Tracking
[301] F. Li, X. Wu, W. Zuo, D.
Zhang, L. Zhang, "Remove Cosine Window from Correlation Filter-based
Visual Trackers: When and How,"
IEEE Trans. on Image Processing, vol. 29, issue 6, pp. 7045-7060, June
2020. (paper) |
[302] W. Zuo, X. Wu, L. Lin, L.
Zhang, M-H. Yang, "Learning Support Correlation Filters for Visual
Tracking," IEEE Trans. on Pattern Analysis
and Machine Intelligence, vol. 41, issue 5, pp.
1158-1172, May 2019.
(paper) (code) |
[303] K. Zhang, L. Zhang, and M. Yang, "Fast Compressive Tracking," IEEE Trans. on Pattern
Analysis and Machine Intelligence, vol. 36, no. 10, pp. 2002-2015, Oct.
2014. (paper) (code and website) (This
is an extension of our CT tracker in ECCV'12) |
[304] K. Zhang, L. Zhang, and M. Yang, "Real-time
Object Tracking via Online Discriminative Feature Selection,"
IEEE Transactions on Image Processing,
vol. 22, no. 12, pp. 4664-4677, Dec. 2013. (paper) (code) |
[305] K. Zhang, L. Zhang, M. Yang, and Q. Hu, "Robust
Object Tracking via Active Feature Selection," IEEE
Transactions on Circuits and Systems for Video Technology, vol. 23, no.
11, pp. 1957-1967, Nov. 2013. (paper) (code) |
[306] J. Ning, L. Zhang, D. Zhang, and W. Yu, "Joint
Registration and Active Contour Segmentation for Object Tracking," IEEE
Transactions on Circuits and Systems for Video Technology, vol. 23, no.
9, pp. 1589 -1597, Sept. 2013. (paper) (code) (website) |
[307] J. Ning, L. Zhang, D. Zhang, and C. Wu,
"Scale and Orientation Adaptive Mean Shift Tracking," IET
Computer Vision, vol. 6, no.1, pp.
62-69, 2012. (paper,
website. code) |
[308] J. Ning, L. Zhang, D. Zhang, and C. Wu, "Robust Mean Shift Tracking
with Corrected Background-Weighted Histogram," IET Computer Vision, vol. 6, no.1, pp. 52-61, 2012. (paper, website. code) (We prove that the background-weighted histogram in the original
mean-shift tracking method is incorrect.) |
[309] J. Ning, L.
Zhang, D. Zhang, and C. Wu, "Robust
Object Tracking using Joint Color-Texture Histogram," International Journal of Pattern Recognition and Artificial
Intelligence, vol. 23, No. 7 (2009) 1245-1263.
(paper,
code) |
Texture
Classification
[310] J. Xie, L. Zhang, J. You and S. Shiu,
"Effective Texture Classification by Texton Encoding Induced Statistical
Features," Pattern Recognition,
vol. 48, issue 2, pp. 447-457, February 2015. (paper) (code) (A very
effective texture classification scheme! The code has
been updated by including the texton learning part.) |
[311] Z. Guo, L. Zhang, and D. Zhang, "A Completed Modeling of Local Binary Pattern
Operator for Texture Classification," IEEE Trans. on Image Processing, vol. 19, no. 6, pp. 1657-1663, June 2010. (paper, matlab code) |
[312] Z. Guo, L. Zhang,
and D. Zhang, "Rotation Invariant
Texture Classification using LBP Variance (LBPV) with Global Matching," Pattern Recognition, vol. 43, no. 3, pp. 706-719, Mar. 2010. (paper, matlab code) |
Biometrics (Finger-knuckle-print,
Palmprint, Fingerprint, Palmvein, etc)
[313] G. Gao, L. Zhang, J. Yang, L. Zhang, and D. Zhang,
"Reconstruction based Finger-Knuckle-Print Verification with Score Level
Adaptive Binary Fusion," IEEE
Transactions on Image Processing, vol. 22, issue 12, pp. 5050-5062, Dec.,
2013. (paper) |
[314] Lin Zhang, Lei Zhang, D. Zhang, and Z. Guo, "Phase
Congruency Induced Local Features for Finger-Knuckle-Print Recognition,"
Pattern Recognition, Volume 45, Issue 7, Pages 2522-2531, July 2012. (paper) (website) |
[315] Lin Zhang, Lei
Zhang, D. Zhang, and H. Zhu, "Ensemble
of Local and Global Information for Finger-Knuckle-Print Recognition," Pattern Recognition, vol. 44, no. 9, pp. 1990-1998, Sep. 2011. (paper) (website) |
[316] Lin Zhang, Lei Zhang, D. Zhang, and H. Zhu,
"Online Finger-Knuckle-Print Verification for Personal
Authentication," Pattern
Recognition,
vol. 43, no. 7, pp. 2560-2571, July 2010. (paper) (website) |
[317] Z. Guo, D. Zhang, L. Zhang, and W. Liu,
"Feature Band Selection for Online Multispectral Palmprint
Recognition," IEEE Trans. on
Information Forensics and Security., vol. 7, issue 3, pp. 1094-1099, Mar.
2012. |
[318] J. Xie, L. Zhang, J. You, D. Zhang, and X. Qu,
"A Study of Hand Back Skin Texture Patterns for Personal Identification
and Gender Classification," Sensors,
Volume 12, Issue 7, Pages 8691-8709, June 2012. (paper) |
[319] W. Li, B.
Zhang, L. Zhang, and J. Yan,
"Principal Line-Based Alignment Refinement for Palmprint
Recognition," IEEE Transactions on System, Man and Cybernetics, Part
C, Volume 42, Issue 6, Pages 1491-1499, Nov. 2012. |
[320] W. Li, D. Zhang, L. Zhang, G. Lu, and J. Yan,
"3-D Palmprint Recognition with Joint Line and Orientation
Features," IEEE Trans. on System, Man and Cybernetics, Part C,
vol. 41, No. 2, pp.274-279, April, 2011. (paper) (database) |
[321] D. Zhang, G. Lu, W. Li, L. Zhang, and N. Luo,
"Palmprint Recognition using 3-D Information," IEEE Trans. System, Man and Cybernetics, Part C, vol. 39, no. 5, pp.
505-519, Sept. 2009. (paper)
(database) |
[322] L. Zhang and D. Zhang, "Characterization of
palmprints by wavelet signatures via directional context modeling," IEEE
Trans. on System, Man and Cybernetic, Part B. vol. 34, pp. 1335-1347, June, 2004. (paper) |
[323] Z. Guo, D. Zhang, L. Zhang, and W. Zuo, "Palmprint Verification using Binary Orientation
Co-occurrence Vector," Pattern Recognition Letters, vol.
30, no. 13, pp. 1219-1227, October, 2009. (paper) |
[324] Z. Guo, W. Zuo, L. Zhang, and D. Zhang, "A Unified Distance Measurement for Orientation
Coding in Palmprint Verification,"
Neurocomputing, Volume 73, pp. 944-950, Issues 4-6, January 2010. (paper) |
[325] D. Zhang, Z. Guo, G. Lu, L. Zhang, and W. Zuo,
"An Online System of Multispectral Palmprint Verification," IEEE Trans. on Instrument and Measurement,
vol. 59, no. 2, pp. 480-490, Feb. 2010. (paper)
(database) |
[326] D. Zhang, Z. Guo, G. Lu, L. Zhang, Y. Liu, and W.
Zuo, "Online Joint Palmprint and Palmvein Verification," Expert System with Applications, vol. 38,
issue 3, pp. 2621-2631, March 2011. (paper) |
[327] Q. Zhao, D. Zhang, L. Zhang, and N. Luo, "Adaptive Fingerprint Pore Modeling and
Extraction," Pattern Recognition,
Volume 43, Issue 8, Pages 2833-2844, August 2010. (paper) (database) |
[328] Q. Zhao, D. Zhang, L. Zhang, and N. Luo, "High resolution partial fingerprint alignment using
pore-valley descriptors", Pattern Recognition, vol. 43, no. 3,
pp. 1050-1061, Mar. 2010. (paper) (database) |
Image Retrieval
and Hashing
[329] S. Jin, H. Yao, X. Sun, S.
Zhou, L. Zhang, X. Hua, "Deep Saliency Hashing for Fine-grained
Retrieval," IEEE Trans. on Image
Processing., vol. 29, issue 3, pp. 5336-5351, Mar. 2020. DOI:
10.1109/TIP.2020.2971105 |
[330] R. Zhang, L. Lin, R. Zhang, W. Zuo, L. Zhang, "Bit-Scalable Deep
Hashing with Regularized Similarity Learning for Image Retrieval and Person
Re-identification," IEEE Trans. on Image Processing, vol.
24, issue 12, pp. 4766-4779, Dec. 2015. (paper) (code) (Bit scalable and deep hashing!) |
[331] X. Zhu, L. Zhang, and Z. Huang, "A Sparse
Embedding and Least Variance Encoding Approach to Hashing," IEEE Trans. on Image Processing, vol.
23, issue 9, pp. 3737- 3750, Sept. 2014. (paper) (code) |
[332] G. Liu, L. Zhang,Y. Hou, Z. Li, and J. Yang,
"Image Retrieval Based on Multi-Texton Histogram," Pattern Recognition, Volume 43, Issue 7, pp. 2380-2389, July 2010. (paper, code) |
[333] G. Liu, Z. Li, L.
Zhang, and Y. Xu, "Image Retrieval based on Micro-structure
Descriptor," Pattern Recognition,
vol. 44, issue 9, pp. 2123-2133,
September 2011. (paper) (code) |
Point and Shape
Matching
[334] W. Lian, L. Zhang, M-H. Yang, "An Efficient Globally Optimal
Algorithm for Asymmetric Point Matching," IEEE Trans. on Pattern Analysis and Machine Intelligence, 2016. (paper) (code&website) |
[335] W. Lian, L. Zhang, and D. Zhang, "Rotation
Invariant Nonrigid Point Set Matching in Cluttered Scenes," IEEE Trans. Image Processing, vol. 21,
issue 5, pp. 2786-2797, May 2012. (paper,
source code) |
[336] W. Lian, L. Zhang, Y. Liang, and Q. Pan,
"A Quadratic Programming based Cluster Correspondence Projection
Algorithm for Fast Point Matching," Computer
Vision and Image Understanding, Vol. 114, Issue 3, pp. 322-333, March
2010. (paper, matlab code) |
Edge Detection
[337] B. Paul, L. Zhang, and X. Wu, "Canny edge
detection enhancement by scale multiplication," IEEE. Trans. on Pattern
Analysis and Machine Intelligence, vol. 27, pp. 1485-1490, Sept. 2005. (paper, matlab code) |
[338] L. Zhang, B. Paul, and X. Wu, "Edge detection
by scale multiplication in wavelet domain," Pattern Recognition
Letters, vol. 23, pp. 1771-1784, 2002. (paper) |
Medical Image Analysis
and Biomedical Engineering
[339] Xi Chen, 40, 111919 (2013). DOI: http://dx.doi.org/10.1118/1.4826173 |
[340] Q. Xu, H. Yu. X. Mou, L. Zhang, H. Jiang, and G.
Wang, "Low-dose X-ray CT Reconstruction via Dictionary Learning," IEEE Transactions on Medical Imaging,
Volume 31, Issue 9, Pages 1682-1697, Sept. 2012. |
[341] B. Zhang, F. Karray, Q. Li, and L. Zhang,
"Sparse Representation Classifier for Microaneurysm Detection and
Retinal Blood Vessel Extraction," Information
Sciences, Volume 200,
Pages 78-90, Oct. 2012. |
[342] Y. Zhao, L.
Zhang, and Q. Pan, "Spectropolarimetric Imaging for Pathological
Analysis of Skin," Applied Optics, vol. 48(10), pp. D236-D246, April 2009. (paper, dataset) |
[343] X. Mou, X. Chen,
L. Sun, H. Yu, Z. Ji, and L. Zhang, "The impact of calibration phantom errors
on dual-energy digital mammography," Phys.
Med. Biol. 53 6321-6336, 2008. (paper) |
[344] L. Zhang, Q. Li,
J. You, and D. Zhang, "A Modified
Matched Filter with Double-Sided Thresholding for Screening Proliferative Diabetic Retinopathy," IEEE Trans. Information Technology in
Biomedicine, vol. 13, no. 4, pp. 528-534, July 2009. (paper) |
[345] Bob Zhang, Lin Zhang, Lei Zhang, and Fakhri Karray, "Retinal
Vessel Extraction by Matched Filter with First-Order Derivative of Gaussian," Computers in Biology and Medicine, Volume 40, Issue 4, April
2010, Pages 438-445. (paper,
matlab code) |
[346] D. Guo, D. Zhang, and L. Zhang, "Sparse
representation-based classification for breath sample identification,"
SENSORS AND ACTUATORS B-CHEMICAL, Vol. 158, No. 1, pp.43-53, 2011. |
[347] D. Guo, D. Zhang, and L. Zhang, "An LDA Based
Sensor Selection Approach Used in Breath Analysis System," SENSORS AND
ACTUATORS B-CHEMICAL, Vol. 157, No. 1, pp.265-274, 2011. |
[348] D. Guo, D. Zhang, N. Li, L. Zhang, and J. Yang,
"A Novel Breath Analysis System Based on Electronic Olfaction" IEEE Trans. on Biomedical Engineering,
vol. 57, no. 11, pp. 2753-2763, Nov. 2010. (paper) |
[349] Y. Chen, L. Zhang, D. Zhang, and D. Zhang, "Wrist Pulse Signal Diagnosis using Modified Gaussian
Models and Fuzzy C-Means Classification," Medical Engineering & Physics, Vol. 31, Issue 10, pp.
1283-1289, Dec. 2009. (paper) |
[350] Y. Chen, L. Zhang, D. Zhang, and D. Zhang, "Computerized Wrist Pulse Signal Diagnosis Using
Modified Auto-Regressive Models,"
Journal
of Medical Systems, Sept. 2009, DOI
10.1007/s10916-009-9368-4. (paper) |
[351] B. Paul and L. Zhang "Noise Reduction for
Magnetic Resonance Images via Adaptive Multiscale Products
Thresholding," IEEE Trans. on Medical Imaging, vol.22, pp.
1089-1099, Sep. 2003. (paper, matlab
code) |
Bioinformatics
[352] C. Zheng, L. Zhang, T. Ng, C. Shiu, and D. Huang,
"Molecular Pattern Discovery Based on Penalized Matrix
Decomposition," IEEE/ACM
Transactions on Computational Biology and Bioinformatics, vol. 8, no. 6, pp. 1592-1603, November/December 2011. (paper,
code) |
[353] C. Zheng, L.
Zhang, T. Ng, and C. Shiu, "Metasample Based Sparse Representation for Tumor
Classification," IEEE/ACM Transactions on Computational Biology and
Bioinformatics, vol. 8, issue 5, pp. 1273 -
1282, Sept.-Oct. 2011. (paper,
code) |
[354] C. Zheng, V. Ng, L. Zhang, C. Shiu, and H. Wang,
"Tumor Classification Based on
Non-negative Matrix Factorization using Gene Expression Data," IEEE Transactions on NanoBioscience,
vol. 10, no. 2, pp. 86-93, June 2011. |
[355] C. Zheng, D.
Huang, L. Zhang, and X. Kong, "Tumor Clustering Using Nonnegative Matrix
Factorization with Gene Selection," IEEE Trans. Information
Technology in Biomedicine, vol. 13, no. 4, pp.599-607,
July 2009. (paper,
code) |
Signal Processing
(Adaptive Filtering, Multi-sensor Data Fusion, etc)
[356] Y. Liang, J. Cao,
Lei Zhang, R. Wang, and Q. Pan, "A
Biologically-Inspired Sensor Wakeup Control Method for Wireless Sensor
Networks," IEEE Trans. on System,
Man and Cybernetics, Part C, vol. 40, issue 5, pp. 525-538, Sept. 2010. (paper) |
[357] L. Zhang and X. Wu, "On the Application of
Cross Correlation Function to Subsample Discrete Time Delay Estimation,"
Digital Signal Processing, 16
(2006), pp. 682-694. (paper) |
[358] L. Zhang, X. Wu, Q. Pan, and H. Zhang,
"Multiresolution modeling and estimation of multisensor data," IEEE
Trans. on Signal Processing, vol. 52, pp. 3170-3182, Nov. 2004. (paper) |
[359] L. Zhang, B. Paul, and X.
Wu, "Wavelet estimation of
fractional Brownian motion embedded in a noisy environment," IEEE
Trans. on Information Theory, vol. 50, pp. 2194-2200, Sept. 2004. (paper) |
[360] L. Zhang, Q. Pan, B. Paul, and H. Zhang, "The
Discrete Kalman Filtering of A Class of Dynamic Multiscale Systems," IEEE
Trans. on Circuits and Systems II: Digital and Analog Signal Processing, vol.49, pp. 668-676, Oct. 2002. (paper) |
Others
(Artificial Intelligence, Lossless Coding)
[361] D. Chen, S. Zhao, L. Zhang, Y. Yang, and X. Zhang,
"Sample
Pair Selection for Attribute Reduction with Rough Set,"
IEEE Transactions on Knowledge and Data Engineering,
Volume 24, Issue 11, Pages 2080-2093, Nov. 2012. |
[362] D. Chen, L. Zhang, S. Zhao, Q. Hu, and P. Zhu,
"A novel algorithm for finding reducts with fuzzy rough sets," IEEE Transactions on Fuzzy Systems, vol. 20, no. 2, pp. 385-389, 2012. |
[363] Q. Hu, L. Zhang, S. An, D.
Zhang, and D. Yu, "On robust fuzzy rough set models," IEEE Transactions on Fuzzy Systems,
vol. 20, no. 4, pp. 636-651, 2012. |
[364] Q. Hu, W. Pan, L. Zhang, D.
Zhang, Y. Song, M. Guo, and D. Yu, "Feature selection for monotonic
classification," IEEE Transactions
on Fuzzy Systems, vol. 20, no. 1, pp. 69-81, 2012. |
[365] Q. Hu, X. Che, L. Zhang, D. Zhang, M. Guo, and D.
Yu, "Rank Entropy Based Decision Trees for Monotonic Classification," IEEE
Transactions on Knowledge and Data Engineering, Volume 24, Issue 11,
Pages 2052-2064, Nov. 2012. |
[366] Q. Hu, L. Zhang, D. Zhang, W. Pan, S. An, and W.
Pedrycz, "Measuring relevance between discrete and continuous features
based on neighborhood mutual information," Expert Systems with Applications, vol. 38, no. 9, pp. 10737-10750, Sept. 2011. |
[367] Q. Hu, L. Zhang, D. Chen, W. Pedrycz, and D. Yu,
"Gaussian Kernel Based Fuzzy Rough Sets: Model, Uncertainty Measures and
Applications," International
Journal of Approximate Reasoning, Volume
51, Issue 4, March 2010,
Pages 453-471. (paper) |
[368] Q. Hu, X. Chen, L. Zhang, and D. Yu, "Feature
Evaluation and Selection Based on Neighborhood Soft Margin," Neurocomputing, Volume 73, Issues 10-12, June 2010, Pages
2114-2124. (paper) |
[369] J. Zhou, X. Wu, and L. Zhang, "ℓ2 Restoration
of ℓ∞-Decoded Images via Soft-Decision Estimation," IEEE Transactions on
Image Processing, Volume 21, Issue 12, Pages 4797-4807, Dec. 2012. |
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