国际期刊

1. Lingxiao He, Haiqing Li, Qi Zhang, and Zhenan Sun, “Dynamic Feature Matching for Partial Face Recognition”, IEEE Trans. on Image Processing, vol. 28, no. 2, pp. 791-802, 2019. 2. Man Zhang, Zhaofeng He, Hui Zhang, Tieniu Tan and Zhenan Sun, “Toward practical remote iris recognition: A boosting based framework,” Neurocomputing, vol.330, pp. 238-252, 2019. 3. Qiang Cui, Shu Wu, Yan Huang, Liang Wang, “A hierarchical contextual attention-based network for sequential recommendation,” Neurocomputing, vol. 358, pp. 141-149, 2019. 4. Yabei Li, Zhang Zhang, Yanhua Cheng, Liang WangandTieniu Tan, “MAPNet: Multi-modal Attentive Pooling Network for RGB-D Indoor Scene Classification,” Pattern Recognition, vol. 90, pp. 436-449, 2019. 5. Yi Li, Lingxiao Song, Xiang Wu, Ran He and Tieniu Tan, “Learning a bi-level adversarial network with global and local perception for makeup-invariant face verification,” Pattern Recognition, vol. 90, pp. 99-108, 2019. 6. Yunbo Wang, Jian Liang, Dong Cao, Zhenan Sun, “Local Semantic-Aware Deep Hashing with Hamming-Isometric Quantization,” IEEE Trans. Image Processing, vol. 28, no. 6, pp. 2665-2679, 2019. 7. Jie Cao, Yibo Hu, Bing Yu, Ran He, Zhenan Sun, “3D Aided Duet GANs for Multi-View Face Image Synthesis,” IEEE Trans. Information Forensics and Security, vol. 14, no. 8, pp. 2028-2042, 2019. 8. Huaibo Huang, Ran He, Zhenan Sun and Tieniu Tan, “Wavelet Domain Generative Adversarial Network for Multi-scale Face Hallucination,” International Journal of Computer Vision, vol. 127, no. 6-7, pp. 763-784, 2019. 9. Feng Yu, Qiang Liu, Shu Wu, Liang Wang and Tieniu Tan, “Attention-Based Convolutional Approach for Misinformation Identification from Massive and Noisy Microblog Posts,” Computers & Security, vol. 83, pp. 106-121, 2019. 10. Jian Liang, Ran He, Zhenan Sun and Tieniu Tan, “Aggregating Randomized Clustering-Promoting Invariant Projections for Domain Adaptation,” IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), vol. 41, no. 5, pp. 1027-1042, 2019. 11. Ran He, Xiang Wu, Zhenan Sun and Tieniu Tan, “Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition,” IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), vol. 41, no. 7, pp. 1761-1773, 2019. 12. Chunshui Cao, Yongzhen Huang, Yi Yang, Liang Wang, Zilei Wang and Tieniu Tan, “Feedback Convolutional Neural Network for Visual Localization and Segmentation,” IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), vol. 41, no. 7, pp. 1627-1640, 2019. 13. Qiyue Yin, Junge Zhang, Shu Wu and Hexi Li, “Multi-view clustering via joint feature selection and partially constrained cluster label learning,”Pattern Recognition, vol. 93, pp. 380-391, 2019. 14. Yupei Wang, Xin Zhao, Xuecai Hu, Yin Li, Kaiqi Huang, “Focal Boundary Guided Salient Object Detection,” IEEE Trans. on Image Processing, vol. 28, no. 6, pp. 2813-2824, 2019. 15. Dangwei Li, Zhang Zhang, Xiaotang Chen, Kaiqi Huang, “A Richly Annotated Pedestrian Dataset for Person Retrieval in Real Surveillance Scenarios,” IEEE Trans. on Image Processing, vol. 28, no. 4, pp. 1575-1590, 2019. 16. Peipei Li, Yibo Hu, Ran He, Zhenan Sun, “Global and Local Consistent Wavelet-Domain Age Synthesis,” IEEE Trans. on Information Forensics and Security, vol. 14, no. 11, pp. 2943-2957, 2019. 17. Hongwen Zhang, Qi Li, Zhenan Sun, “Adversarial Learning Semantic Volume for 2D/3D Face Shape Regression in the Wild,” IEEE Trans. on Image Processing, vol. 28, no. 9, pp. 4526-4540, 2019. 18. Hanzhou Wu, Wei Wang, Jing Dong and Hongxia Wang, “New Graph-Theoretic Approach to Social Steganography,” Electronic Imaging, pp. 539-1-539–6, 2019. 19. Yuqi Zhang, Yongzhen Huang, Liang Wang, Shiqi Yu, “A comprehensive study on gait biometrics via a joint CNN-based method,” Pattern Recognition, vol. 93, pp. 228-236, 2019. 20. Yanyun Wang, Chunfeng Song, Yan Huang, Zhenyu Wang, Liang Wang, “Learning View Invariant Gait Features with Two-Stream GAN,” Neurocomputing, vol. 339, pp. 245-254, 2019. 21. Linjiang Huang, Yan Huang, Wanli Ouyang, Liang Wang, “Part-Aligned Pose-Guided Recurrent Network for Action Recognition,” Pattern Recognition, vol. 92, pp. 162-176, 2019. 22. Da Li, Zhang Zhang, Kai Yu, Kaiqi Huang and Tieniu Tan, “ISEE: An Intelligent Scene Exploration and Evaluation Platform for Large-Scale Visual Surveillance,” IEEE Trans. on Parallel and Distributed Systems, vol. 30, no.12, pp. 2743-2758. 23. Zhanyu Ma, Yuping Lai, W. Bastiaan Kleijn, Yi-Zhe Song, Liang Wang, Jun Guo, “Variational Bayesian Learning for Dirichlet Process Mixture of Inverted Dirichlet Distributions in Non-Gaussian Image Feature Modeling,” IEEE Trans. on Neural Networks and Learning Systems, vol. 30, no. 2, pp. 449-463, 2019. 24. Jie Liang, Jufeng Yang, Ming-Ming Cheng, Paul L. Rosin and Liang Wang, “Simultaneous Subspace Clustering and Cluster Number Estimating based on Triplet Relationship,” IEEE Trans. on Image Processing, vol. 28, no.8, pp. 3973-3985, 2019. 25. Yan Huang, Jingsong Xu, Qiang Wu, Zhedong Zheng, Zhaoxiang Zhang*, Jian Zhang, “Multi-Pseudo Regularized Label for Generated Data in Person Re-Identification,” IEEE Trans. on Image Processing, vol. 28, no. 3, pp. 1391-1403, 2019. 26. Wei Wang, Hao Wang, Zhaoxiang Zhang, Chen Zhang and Yang Gao, “Semi-supervised domain adaptation via Fredholm integral based kernel methods,” Pattern Recognition, vol. 85, pp. 185-197, 2019. 27. Xinwei He, Baoguang Shi, Xiang Bai, Gui-Song Xia, Zhaoxiang Zhang and Weisheng Dong, “Image Caption Generation with Part of Speech Guidance,” Pattern Recognition Letters, vol. 119, pp. 229-237, 2019. 28. Ce Li, Xinyu Zhao, Zhaoxiang Zhang and Shaoyi Du, “Generative adversarial dehaze mapping nets,” Pattern Recognition Letters, vol. 119, pp. 238-244, 2019. 29. Heikki Huttunen, Ke Chen and Zhaoxiang Zhang, “Guest Editorial: Special Issue on Machine Learning Implementations,” Signal Processing Systems, vol. 91, no. 2, pp. 115-116, 2019. 30. Xiuchun Xiao, Neal N. Xiong, Jianhuang Lai, Chang-Dong Wang, Zhenan Sun and Jingwen Yan, “A Local Consensus Index Scheme for Random-Valued Impulse Noise Detection Systems,” IEEE Trans. on Systems, Man, and Cybernetics: Systems, pp. 1-17, 2019. 31. Wangli Hao and Zhaoxiang Zhang, “Spatiotemporal distilled dense-connectivity network for video action recognition,” Pattern Recognition, vol.92, pp. 13-24, 2019. 32. Guibo Zhu, Zhaoxiang Zhang, Jinqiao Wang, Yi Wu and Hanqing Lu, “Dynamic Collaborative Tracking,” IEEE Trans. on Neural Networks and Learning Systems, vol.30, pp. 3035-3046, 2019.

国际会议

1. Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, Tieniu Tan, “Session-based Recommendation with Graph Neural Network,” Proc. AAAI Conference on Artificial Intelligence, pp. 346-353,January 2019, Hawaii, USA. 2. Yan Huang, Yang Long, and Liang Wang, “Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding,” Proc. AAAI Conference on Artificial Intelligence, pp. 8489-8496, January 2019, Hawaii, USA. 3. Xiang Wu, Huaibo Huang, Vishal Patel, Ran He and Zhenan Sun, “Disentangled Variational Representation for Heterogeneous Face Recognition,” Proc. AAAI Conference on Artificial Intelligence, pp. 9005-9012, January 2019, Hawaii, USA. 4. Linsen Song, Jie Cao, Lingxiao Song, Yibo Hu and Ran He, “Geometry-Aware Face Completion and Editing,” Proc. AAAI Conference on Artificial Intelligence, January 2019, Hawaii, USA. 5. Qiaozhe Li, Xin Zhao, Ran He and Kaiqi Huang, “Visual-semantic Graph Reasoning for Pedestrian Attribute Recognition,” Proc. AAAI Conference on Artificial Intelligence, pp. 8634-8641, January 2019, Hawaii, USA. 6. Wenkai Dong, Zhaoxiang Zhang and Tieniu Tan, “Attention-aware Sampling via Deep Reinforcement Learning for Action Recognition,” Proc. AAAI Conference on Artificial Intelligence, pp. 8247-8254, January 2019, Hawaii, USA. 7. Qing En, Lijuan Duan, Zhaoxiang Zhang, Xiang Bai, Yundong Zhang, “Human-like Delicate Region Erasing Strategy for Weakly Supervised Detection,” Proc. AAAI Conference on Artificial Intelligence, January 2019, Hawaii, USA. 8. Caiyong Wang, Yong He, Yunfan Liu, Zhaofeng He, Ran He and Zhenan Sun, “ScleraSegNet: an Improved U-Net Model with Attention for Accurate Sclera Segmentation,” Proc. International Conference on Biometrics, June 2019, Crete, Greece. 9. Min Ren, Caiyong Wang, Yunlong Wang, Zhenan Sun and Tieniu Tan, “Alignment Free and Distortion Robust Iris Recgnition,” Proc. International Conference on Biometrics, June 2019, Crete, Greece. 10. Yunfan Liu, Qi Li and Zhenan Sun, “Attribute-aware Face Aging with Wavelet-based Generative Adversarial Networks,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 11877-11886, June 2019, Long Beach, CA, USA. 11. Weining Wang, Yan Huang and Liang Wang, “Language-Driven Temporal Activity Localization: A Semantic Matching Reinforcement Learning Model,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 334-343, June 2019, Long Beach, CA, USA. 12. Chunfeng Song, Yan Huang, Wanli Ouyang and Liang Wang, “Box-Driven Class-Wise Region Masking and Filling Rate Guided Loss for Weakly Supervised Semantic Segmentation,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 3136-3145, June 2019, Long Beach, CA, USA. 13. Chenyang Si, Wentao Chen, Wei Wang, Liang Wang and Tieniu Tan, “An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 1227-1236, June 2019, Long Beach, CA, USA. 14. Xuecai Hu, Haoyuan Mu, Xiangyu Zhang, Zilei Wang, Tieniu Tan and Jian Sun, “Meta-SR: A Magnification-Arbitrary Network for Super-Resolution,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 1575-1584, June 2019, Long Beach, CA, USA. 15. Jian Liang, Ran He, Zhenan Sun and Tieniu Tan, “Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation,” Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 2975-2984, June 2019, Long Beach, CA, USA. 16. Fenyu Hu, Yanqiao Zhu, Shu Wu, Liang Wang, Tieniu Tan, “Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification,” Proc. International Joint Conference on Artificial Intelligence (IJCAI), pp. 4532-4539, August 2019, Macao, China. 17. Qiaozhe Li, Xin Zhao, Ran He, Kaiqi Huang, “Pedestrian Attribute Recognition by Joint Visual-semantic Reasoning and Knowledge Distillation,” Proc. International Joint Conference on Artificial Intelligence (IJCAI), pp. 833-839, August 2019, Macao, China. 18. Zeyu Cui, Zekun Li, Shu Wu, Xiaoyu Zhang, Liang Wang, “Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks,” Proc. the web conference, pp. 307-317, May 2019, San Francisco, USA. 19. Yi Li, Huaibo Huang, Junchi Yu, Ran HeandTieniu Tan, “Cosmetic-Aware Makeup Cleanser,” Proc. IEEE International Conference on Biometrics: Theory, Applications, and Systems, September 2019, Tampa, Florida, USA. 20. Jianze Wei, Yunlong Wang, Xiang Wu, Zhaofeng He, Ran He, Zhenan Sun, “Cross-Sensor Iris Recognition Using Adversarial Strategy and Sensor-Specific Information,” Proc. IEEE International Conference on Biometrics: Theory, Applications, and Systems, September 2019, Tampa, Florida. 21. Junbo Wang, Wei Wang, Zhiyong Wang, Liang Wang, Dagan FengandTieniu Tan, “Stacked Memory Network for Video Summarization,” Proc. ACM Multimedia Conference, October 2019, Nice, France. 22. Hongwen Zhang, Jie Cao, Guo Lu, Wanli Ouyang and Zhenan Sun, “DaNet: Decompose-and-aggregate Network for 3D Human Shape and Pose Estimation” Proc. ACM Multimedia Conference, October 2019, Nice, France. 23. Yan Huang and Liang Wang,“ACMM: Aligned Cross-Modal Memory for Few-Shot Image and Sentence Maching,” Proc. IEEE International Conference on Computer Vision,October 2019, Seoul, Korea. 24. Yanghao Li, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang,“Scale-aware trident networks for object detection,”Proc. IEEE International Conference on Computer Vision, October 2019, Seoul, Korea. 25. Haiping Wu, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang,“Sequence Level Semantics Aggregation for Video Object Detection,”Proc. IEEE International Conference on Computer Vision, October 2019, Seoul, Korea. 26. Chuanchen Luo, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang,“Spectral Feature Transformation for Person Re-identification,”Proc. IEEE International Conference on Computer Vision, October 2019, Seoul, Korea. 27. Peipei Li, Xiang Wu, Yibo Hu, Ran He and Zhenan Sun,“M2FPA: A Multi-Yaw Multi-Pitch High-Quality Database and Benchmark for Facial Pose Analysis,”Proc. IEEE International Conference on Computer Vision, October 2019, Seoul, Korea. 28. Junran Peng, Ming Sun, Zhaoxiang Zhang*, Tieniu Tan, Junjie Yan, “Efficient Neural Architecture Transformation Searchin Channel-Level for Object Detection,” Proc. Conference on Neural Information Processing Systems (NIPS), December 2019, Vancouver, Canada. 29. Junran Peng, Ming Sun, Zhaoxiang Zhang*, Tieniu Tan, Junjie Yan, “POD: Practical Object Detection with Scale-Sensitive Network,” Proc. IEEE International Conference on Computer Vision, pp. 9607-9616, October 2019, Seoul, Korea. 30. Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang and Ran He, “Dual Variational Generation for Low Shot Heterogeneous Face Recognition,” Proc. Conference on Neural Information Processing Systems (NIPS), December 2019, Vancouver, Canada. 31. Da Li, Dangwei Li, Zhang Zhang, Liang Wang and Tieniu Tan, “Unsupervised Cross-Domain Person Re-Identification: A New Framework.” Proc. IEEE International Conference on Image Processing, September 2019, Taiwan. 32. Yi Fan Song, Zhang Zhang and Liang Wang, “Richly Activated Graph Convolutional Network For Action Recognition With Incomplete Skeletons,” Proc. IEEE International Conference on Image Processing, September 2019, Taiwan. 33. Zerui Chen,Yan Huang and Liang Wang, “Augmented Visual-Semantic Embeddings for Image And Sentence Matching,” Proc. IEEE International Conference on Image Processing, September 2019, Taiwan. 34. Tianxiang Ma, Bo Peng, Wei Wang, Jing Dong, “Any-to-one Face Reenactment Based on Conditional Generative Adversarial Network,”Proc. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, pp. 1657-1664, November 2019, Lanzhou, China. 35. Qiyue Yin, Qingming Li, Junge Zhang, Shu Wu, “Multi-view clustering via adversarial view embedding and adaptive view fusion,” Proc. ACM International Conference on Information and Knowledge Management (CIKM), November 2019, BeijingChina. 36. Qiang Cui, Yuyuan Tang, Shu Wu and Liang Wang, “Distance2Pre: Personalized Spatial Preference for Next Point-of-Interest Prediction,” Proc. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 289-301, April 2019, Macau, China. 37. Linjiang Huang, Yan Huang, Wanli Ouyang and Liang Wang, “Hierarchical Graph Convolutional Network For Skeleton-Based Action Recognition,”International Conference on Image and Graphics (ICIG), August 2019, Beijing, China. 38. Kai Niu, Yan Huang and Liang Wang, “Fusing Two Directions in Cross-domain Adaption for Real Life Person Search by Language,” Proc. IEEE International Conference on Computer Vision Workshop, October 2019, Seoul, Korea. 39. Hongyuan Yu, Chengquan Zhang, Xuan Li, Junyu Han, Errui Ding, Liang Wang, “An End-to-end Video Text Detector with Online Tracking,” Proc. International Conference on Document Analysis and Recognition (ICDAR), September 2019, Sydney, Australia. 40. Zerui Chen, Yan Huang, Liang Wang, “Learning Depth-aware Heatmaps for 3D Human Pose Estimation in the Wild,” Proc. British Machine Vision Conference (BMVC), September 2019, Cardiff, Wales, UK. 41. Wu Zheng, Lin Li, Zhaoxiang Zhang, Yan Huang, and Liang Wang, “Relational Network for Skeleton-Based Action Recognition,” Proc. IEEE International Conference on Multimedia and Expo (ICME), July 2019, Shanghai, China. 42. Weikuo Guo, Huaibo Huang, Xiangwei Kong, Ran He, “Learning Disentangled Representation for Cross-Modal Retrieval with Deep Mutual Information Estimation,” Proc. ACM International Conference on Multimedia, October 2019, Nice, France. 43. Chaoyou Fu, Liangchen Song, Xiang Wu, Guoli Wang, Ran He, “Neurons Merging Layer: Towards Progressive Redundancy Reduction for Deep Supervised Hashing,” Proc. International Joint Conference on Artificial Intelligence, August 2019, Macao, China. 44. Junchi Yu, Jie Cao, Yi Li, Xiaofei Jia, Ran He, “Pose-preserving Cross Spectral Face Hallucination,” Proc. International Joint Conference on Artificial Intelligence,” August 2019, Macao, China. 45. Chufeng Tang, Lu Sheng, Zhaoxiang Zhang, Xiaolin Hu, “Improving Pedestrian Attribute Recognition with Weakly-Supervised Multi-scale Attribute-Specific Localization,” Proc. IEEE International Conference on Computer Vision, October 2019, Seoul, Korea. 46. Lingxiao He, Yinggang Wang, Wu Liu, He Zhao, Zhenan Sun, Jiashi Feng, “Foreground-Aware Pyramid Reconstruction for Alignment-Free Occluded Person Re-Identification,” Proc. IEEE International Conference on Computer Vision, pp. 8450-8459, October 2019, Seoul, Korea. 47. Zekun Li, Zeyu Cui, Shu Wu, Xiaoyu Zhang, Liang Wang, “Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction,” Proc. ACM International Conference on Information and Knowledge Management (CIKM), November 2019, Beijing, China. 48. Jingyi Wang, Qiang Liu, Zhaocheng Liu, Shu Wu, “Towards Accurate and Interpretable Sequential Prediction: A CNN & Attention-Based Feature Extractor,” Proc. ACM International Conference on Information and Knowledge Management (CIKM), November 2019, BeijingChina. 49. Zekun Li, Zeyu Cui, Shu Wu, Xiaoyu Zhang, Liang Wang, “Semi-supervised Compatibility Learning across Categories for Clothing Matching,” Proc. IEEE International Conference on Multimedia and Expo (ICME), July 2019, Shanghai, China.

国内会议

1. X. Xuan, B. Peng, W. Wang and J. Dong, “On the Generalization of GAN Image Forensics,” Proc. Chinese Conference on Biometric Recognition, pp. 134–141, October 2019, Hunan, China. 2. M. Bian, B. Peng, W. Wang and J. Dong, “An Accurate LSTM Based Video Heart Rate Estimation Method,” Proc. Chinese Conference on Pattern Recognition and Computer Vision (PRCV), pp. 409–417, November 2019, Xi’an China. 3. Mingyun Bian, Bo Peng, Wei Wang and Jing Dong, “An Accurate LSTM Based Video Heart Rate Estimation Method,” Proc. Chinese Conference on Pattern Recognition and Computer Vision (PRCV), pp. 409–417, November 2019, Xi’an China. 4. Hongyuan Yu, Yan Huang, Lihong Pi, Liang Wang, “Recurrent Deconvolutional Generative Adversarial Networks with Application to Video Generation,” Proc. Chinese Conference on Pattern Recognition and Computer Vision (PRCV), November 2019, Xi’an China.