To date, I have published 2 PAMI, 1 IJCV, 3 NIPS, 1 ICLR, 8 CVPR, 4 ICCV, 3 ECCV, 2 MM, 1 ICDM, 25 in total. All my publications can be downloaded from my Google Scholar profile. Please send me an email with any problem.


2021

P47. Yiming Zhao, Xinming Huang, and Ziming Zhang. Deep Lucas-Kanade Homography for Multimodal Image Alignment. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2021.

P46. Yiming Zhao, Lin Bai, Ziming Zhang, and Xinming Huang. A Surface Geometry Model for LiDAR Depth Completion. IEEE Robotics and Automation Letters, 2021.

2020

P45. Feiyun Cui, Yun Yue, Yi Zhang, Ziming Zhang, and H. Susan Zhou. Advancing Biosensors with Machine Learning. ACS Sensors, 2020.

P44. Ziming Zhang. An Efficient Empirical Solver for Localized Multiple Kernel Learning via DNNs. In Proceeding of International Conference on Pattern Recognition (ICPR), 2020.

P43. Yun Yue, Ming Li, Venkatesh Saligrama, and Ziming Zhang. RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm. In Proceeding of International Conference on Pattern Recognition (ICPR), 2020.

P42. Yecheng Lyu, Ming Li, Xinming Huang, Ulkuhan Guler, Patrick Schaumont, and Ziming Zhang. TreeRNN: Topology-Preserving Deep Graph Embedding and Learning. In Proceeding of International Conference on Pattern Recognition (ICPR), 2020.

P41. Xin Zhang, Yanhua Li, Ziming Zhang, and Zhi-Li Zhang. f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning. In Proceeding of Advances in Neural Information Processing Systems (NeurIPS), 2020.

P40. Xin Zhang, Yanhua Li, Xun Zhou, Ziming Zhang, and Jun Luo. TrajGAIL: Trajectory Generative Adversarial Imitation Learning for Long-term Decision Analysis. In Proceeding of International Conference on Data Mining (ICDM), 2020.

P39. Keshav Bimbraw, Xihan Ma, Ziming Zhang, and Haichong Zhang. Augmented Reality-Based Lung Ultrasound Scanning Guidance. In Proceeding of Workshop on Advances in Simplifying Medical UltraSound (ASMUS), Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020.

P38. Ce Zheng, Yecheng Lyu, Ming Li, and Ziming Zhang. LodoNet: A Deep Neural Network with 2D Keypoint Matching for 3D LiDAR Odometry Estimation. In Proceeding of ACM International Conference on Multimedia (ACM MM), 2020.

P37. Yecheng Lyu, Xinming Huang, and Ziming Zhang. Learning to Segment 3D Point Clouds in 2D Image Space. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2020. (oral)

P36. Anil Kag, Ziming Zhang, and Venkatesh Saligrama. RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? In Proceeding of International Conference on Learning Representations (ICLR), 2020.

P35. Ziming Zhang, Wenchi Ma, Yuanwei Wu, and Guanghui Wang. Self-Orthogonality Module: A Network Architecture Plug-in for Learning Orthogonal Filters. In Proceeding of Winter Conference on Applications of Computer Vision (WACV), 2020.

P34. Wenju Xu, Guanghui Wang, Alan Sullivan, and Ziming Zhang. Towards Learning Affine-Invariant Representations via Data-Efficient CNNs. In Proceeding of Winter Conference on Applications of Computer Vision (WACV), 2020.

P33. Mahdi Elhousni, Yecheng Lyu, Xinming Huang, and Ziming Zhang. Automatic Building and Labeling of HD Maps with Deep Learning. In Proceeding of Thirty-Second Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2020.


2019

P32. Yao Sui, Ziming Zhang, Guanghui Wang, Yafei Tang, and Li Zhang. Exploiting the Anisotropy of Correlation Filter Learning for Visual Tracking. International Journal of Computer Vision (IJCV), 2019.

P31. Yuanwei Wu, Ziming Zhang, and Guanghui Wang. Unsupervised Deep Feature Transfer for Low Resolution Image Classification. In Proceeding of Workshop and Challenge on Real-World Recognition from Low-Quality Images and Videos, International Conference on Computer Vision (ICCV), 2019.


2018

P30. Jian Zheng, Teng-Yok Lee, Chen Feng, Xiaohua Li, and Ziming Zhang. Robust Attentional Pooling via Feature Selection. In Proceeding of International Conference on Pattern Recognition (ICPR), 2018.

P29. Ziming Zhang, Yuanwei Wu, and Guanghui Wang. BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2018.


2017

P28. Ziming Zhang, Yun Liu, Xi Chen, Yanjun Zhu, Ming-Ming Cheng, Venkatesh Saligrama, and Philip H.S. Torr. Sequential Optimization for Efficient High-Quality Object Proposal Generation. IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), 2017.

P27. Ziming Zhang, and Matthew Brand. Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks. In Proceeding of Advances in Neural Information Processing Systems (NIPS), 2017.

P26. Chiori Hori, Takaaki Hori, Teng-Yok Lee, Ziming Zhang, Bret Harsham, John R. Hershey, Tim K. Marks, and Kazuhiro Sumi. Attention-Based Multimodel Fusion for Video Description. In Proceeding of International Conference on Computer Vision (ICCV), 2017.


2016

P25. Ziming Zhang, and Philip H.S. Torr. Object Proposal Generation using Two-Stage Cascade SVMs. IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), 2016.

P24. Ziming Zhang, and Venkatesh Saligrama. PRISM: Person Re-Identification via Structured Matching. IEEE Transaction on Circuits and Systems for Video Technology (TCSVT), June 2016.

P23. Ziming Zhang, and Venkatesh Saligrama. Zero-Shot Recognition via Structured Prediction. In Proceeding of European Conference on Computer Vision (ECCV), 2016.

P22. Yao Sui, Ziming Zhang, Guanghui Wang, Yafei Tang, and Li Zhang. Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning. In Proceeding of European Conference on Computer Vision (ECCV), 2016.

P21. Ziming Zhang, Yuting Chen, and Venkatesh Saligrama. Efficient Training of Very Deep Neural Networks for Supervised Hashing. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2016.

P20. Ziming Zhang, and Venkatesh Saligrama. Zero-Shot Learning via Joint Latent Similarity Embedding. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2016.


2015

P19. Ziming Zhang, and Venkatesh Saligrama. Zero-Shot Learning via Semantic Similarity Embedding. In Proceeding of International Conference on Computer Vision (ICCV), 2015.

P18. Ziming Zhang, Yuting Chen, and Venkatesh Saligrama. Group Membership Prediction. In Proceeding of International Conference on Computer Vision (ICCV), 2015.

P17. Gregory D. Castanon, Yuting Chen, Ziming Zhang, and Venkatesh Saligrama. Efficient Activity Retrieval through Semantic Graph Queries. In Proceeding of ACM International Conference on Multimedia (ACM MM), 2015: 391-400. (oral)

P16. Ziming Zhang, and Venkatesh Saligrama. RAPID: Rapidly Accelerated Proximal Gradient Algorithms for Convex Minimization. In Proceeding of International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015.


2014

P15. Ziming Zhang, Heng Huang, and Dinggang Shen. Integrative Analysis of Multi-Dimensional Imaging Genomics Data for Alzheimer’s Disease Prediction. Frontiers in Aging Neuroscience, 2014.

P14. Ziming Zhang, Yuting Chen, and Venkatesh Saligrama. A Novel Visual Word Co-occurrence Model for Person Re-identification In ECCV Workshop on Visual Surveillance and Re-Identification, 2014.

P13. Ming-Ming Cheng, Ziming Zhang, Wen-Yan Lin, and Philip H.S. Torr. BING: Binarized normed gradients for objectness estimation at 300fps. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2014. (oral)


2012

P12. Ziming Zhang, Paul Sturgess, Sunando Sengupta, Nigel Crook, and Philip H.S. Torr. Efficient Discriminative Learning of Parametric Nearest Neighbor Classifiers. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2012.


2011

P11. Ziming Zhang, Lubor Ladicky, Philip H.S. Torr, and Amir Saffari. Learning Anchor Planes for Classification. In Proceeding of Advances in Neural Information Processing Systems (NIPS), 2011: 1611-1619.

P10. Ziming Zhang, Jonathan Warrell, and Philip H.S. Torr. Proposal Generation for Object Detection using Cascaded ranking SVMs. In Proceeding of Computer Vision and Pattern Recognition (CVPR), 2011: 1497-1504.

P9. Ziming Zhang, Jiawei Huang, and Ze-Nian Li. Learning Sparse Features On-Line for Image Classification. In Proceeding of International Conference on Image Analysis and Recognition (ICIAR), 2011: 122-131. (oral)


2010

P8. Ziming Zhang, Jiawei Huang, and Ze-Nian Li. Discovering Motion Patterns for Human Action Recognition. In Proceeding of Pacific-Rim Conference on Multimedia (PCM), 2010: 716-727.

P7. Ziming Zhang, Ze-Nian Li, and Mark Drew. Learning Image Similarities via Probabilistic Feature Matching. In Proceeding of International Conference on Image Processing (ICIP), 2010: 1857-1860. (oral)

P6. Ziming Zhang, Ze-Nian Li, and Mark Drew. AdaMKL: A Novel Biconvex Multiple Kernel Learning Approach. In Proceeding of International Conference on Pattern Recognition (ICPR), 2010: 2126-2129. (oral)


2009

P5. Ziming Zhang, Ze-Nian Li, and Mark Drew. Feature Correspondence with Constrained Global Structures. In Proceeding of International Conference on Image Processing (ICIP), 2009: 177-180.


2008

P4. Ziming Zhang, Yiqun Hu, Syin Chan, and Liang-Tien Chia. Motion Context: A New Representation for Human Action Recognition. In Proceeding of European Conference on Computer Vision (ECCV), 2008: 817-829.


2007

P3. Ziming Zhang, Syin Chan, and Liang-Tien Chia. Image Classification Using Tensor Representation. In Proceeding of ACM International Conference on Multimedia (MM), 2007: 281-284.

P2. Ziming Zhang, Syin Chan, and Liang-Tien Chia. Discriminative Signatures for Image Classification. In Proceeding of International Conference on Image Processing (ICIP), 2007: 197-200.

P1. Ziming Zhang, Syin Chan, and Liang-Tien Chia. Codebook+: A New Module for Creating Discriminative Codebooks. In Proceeding of International Conference on Multimedia and Expo (ICME), 2007: 815-818.