Crowded scene analysis: A survey T Li, H Chang, M Wang, B Ni, R Hong, S Yan IEEE transactions on circuits and systems for video technology 25 (3), 367-386, 2014 | 548 | 2014 |
Adversarial domain adaptation with domain mixup M Xu, J Zhang, B Ni, T Li, C Wang, Q Tian, W Zhang Proceedings of the AAAI conference on artificial intelligence 34 (04), 6502-6509, 2020 | 424 | 2020 |
Peak-piloted deep network for facial expression recognition X Zhao, X Liang, L Liu, T Li, Y Han, N Vasconcelos, S Yan Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 362 | 2016 |
Contextual bag-of-words for visual categorization T Li, T Mei, IS Kweon, XS Hua IEEE Transactions on Circuits and Systems for Video Technology 21 (4), 381-392, 2010 | 202 | 2010 |
Dense crowd counting from still images with convolutional neural networks Y Hu, H Chang, F Nian, Y Wang, T Li Journal of Visual Communication and Image Representation 38, 530-539, 2016 | 133 | 2016 |
Facial expression recognition with faster R-CNN J Li, D Zhang, J Zhang, J Zhang, T Li, Y Xia, Q Yan, L Xun Procedia Computer Science 107, 135-140, 2017 | 122 | 2017 |
Pornographic image detection utilizing deep convolutional neural networks F Nian, T Li, Y Wang, M Xu, J Wu Neurocomputing 210, 283-293, 2016 | 86 | 2016 |
Robust face anti-spoofing with depth information Y Wang, F Nian, T Li, Z Meng, K Wang Journal of Visual Communication and Image Representation 49, 332-337, 2017 | 74 | 2017 |
Contrastive regression for domain adaptation on gaze estimation Y Wang, Y Jiang, J Li, B Ni, W Dai, C Li, H Xiong, T Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 55 | 2022 |
A cascade 3D U‐Net for dose prediction in radiotherapy S Liu, J Zhang, T Li, H Yan, J Liu Medical physics 48 (9), 5574-5582, 2021 | 49 | 2021 |
Shape self-correction for unsupervised point cloud understanding Y Chen, J Liu, B Ni, H Wang, J Yang, N Liu, T Li, Q Tian Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 47 | 2021 |
A novel image denoising algorithm using linear Bayesian MAP estimation based on sparse representation D Sun, Q Gao, Y Lu, Z Huang, T Li Signal Processing 100, 132-145, 2014 | 42 | 2014 |
Vision-based UAV Navigation in Mountain Area. J Woo, K Son, T Li, GS Kim, IS Kweon MVA, 236-239, 2007 | 40 | 2007 |
Convolutional residual‐attention: A deep learning approach for precipitation nowcasting Q Yan, F Ji, K Miao, Q Wu, Y Xia, T Li Advances in Meteorology 2020 (1), 6484812, 2020 | 35 | 2020 |
Predicting voxel-level dose distributions for esophageal radiotherapy using densely connected network with dilated convolutions J Zhang, S Liu, H Yan, T Li, R Mao, J Liu Physics in Medicine & Biology 65 (20), 205013, 2020 | 32 | 2020 |
License plate localization in unconstrained scenes using a two-stage CNN-RNN J Zhang, Y Li, T Li, L Xun, C Shan IEEE Sensors Journal 19 (13), 5256-5265, 2019 | 32 | 2019 |
Learning explicit video attributes from mid-level representation for video captioning F Nian, T Li, Y Wang, X Wu, B Ni, C Xu Computer Vision and Image Understanding 163, 126-138, 2017 | 32 | 2017 |
Hidden-concept driven multilabel image annotation and label ranking BK Bao, T Li, S Yan IEEE Transactions on Multimedia 14 (1), 199-210, 2011 | 31 | 2011 |
On random hyper-class random forest for visual classification T Li, B Ni, X Wu, Q Gao, Q Li, D Sun Neurocomputing 172, 281-289, 2016 | 29 | 2016 |
Vehicle counting in crowded scenes with multi-channel and multi-task convolutional neural networks M Sun, Y Wang, T Li, J Lv, J Wu Journal of Visual Communication and Image Representation 49, 412-419, 2017 | 28 | 2017 |