| ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes T Xiao, J Hong, J Ma Proceedings of the European Conference on Computer Vision (ECCV), 172--187, 2018 | 221 | 2018 |
| Genegan: Learning object transfiguration and attribute subspace from unpaired data S Zhou, T Xiao, Y Yang, D Feng, Q He, W He Proceedings of the British Machine Vision Conference (BMVC), 2017 | 110 | 2017 |
| DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images T Xiao, J Hong, J Ma International Conference on Learning Representations Workshop (ICLR), 2018 | 86 | 2018 |
| Adversarial Learning of Privacy-Preserving and Task-Oriented Representations T Xiao, YH Tsai, K Sohn, M Chandraker, MH Yang AAAI Conference on Artificial Intelligence (AAAI), 2020 | 82 | 2020 |
| Adaptive transformers for robust few-shot cross-domain face anti-spoofing HP Huang, D Sun, Y Liu, WS Chu, T Xiao, J Yuan, H Adam, MH Yang European conference on computer vision, 37-54, 2022 | 55 | 2022 |
| Learning Contrastive Representation for Semantic Correspondence T Xiao, S Liu, S De Mello, Z Yu, J Kautz, MH Yang International Journal of Computer Vision, 1-17, 2022 | 15 | 2022 |
| Learnable Cost Volume Using the Cayley Representation T Xiao, J Yuan, D Sun, Q Wang, XY Zhang, K Xu, MH Yang Proceedings of the European Conference on Computer Vision (ECCV), 2020 | 14 | 2020 |
| Semi-Supervised Learning with Meta-Gradient XY Zhang, T Xiao, H Jia, MM Cheng, MH Yang International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021 | 10* | 2021 |
| Exploiting Category Names for Few-Shot Classification with Vision-Language Models T Xiao, Z Wang, L Cao, J Yu, S Dai, MH Yang International Conference on Learning Representations Workshop (ICLR), 2023 | 3 | 2023 |
| Learning contrastive representation for semantic correspondence T Xiao, S Liu, S De Mello, Z Yu, J Kautz US Patent 20230074706A1, 2023 | 2 | 2023 |
| Iqnn: Training quantized neural networks with iterative optimizations S Zhou, H Wen, T Xiao, X Zhou Artificial Neural Networks and Machine Learning–ICANN 2017: 26th …, 2017 | 2 | 2017 |
| FlowNAS: Neural Architecture Search for Optical Flow Estimation Z Lin, T Liang, T Xiao, Y Wang, Z Tang, MH Yang International Journal of Computer Vision, 2023 | 1 | 2023 |
| Correction to: Learning Contrastive Representation for Semantic Correspondence T Xiao, S Liu, S De Mello, Z Yu, J Kautz, MH Yang International Journal of Computer Vision 130 (6), 1607-1607, 2022 | 1 | 2022 |
| Structured Sparsification with Joint Optimization of Group Convolution and Channel Shuffle XY Zhang, K Zhao, T Xiao, MM Cheng, MH Yang Conference on Uncertainty in Artificial Intelligence (UAI), 2021 | 1 | 2021 |
| Learning Correspondence from Images, Videos and Texts T Xiao UC Merced, 2023 | | 2023 |
| Learnable cost volume for determining pixel correspondence T Xiao, D Sun, MH Yang, Q Wang, J Yuan US Patent 11790550B2, 2022 | | 2022 |
| Learning Contrastive Representation for Semantic Correspondence (Apr, 10.1007/s11263-022-01602-y, 2022) T Xiao, S Liu, S De Mello, Z Yu, J Kautz, MH Yang INTERNATIONAL JOURNAL OF COMPUTER VISION 130 (6), 1607-1607, 2022 | | 2022 |
| An Integrated Learning Framework for Pedestrian Tracking T Xiao, J Ma Intelligent Computing Methodologies: 13th International Conference, ICIC …, 2017 | | 2017 |
| Introduction to Hypergeometric Transformations T Xiao | | |
Ming-Hsuan YangUniversity of California at Merced; Google DeepMind在 ucmerced.edu 的电子邮件经过验证
