| Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems T Chen, M Li, Y Li, M Lin, N Wang, M Wang, T Xiao, B Xu, C Zhang, ... arXiv preprint arXiv:1512.01274, 2015 | 2760 | 2015 |
| Deep graph library: A graph-centric, highly-performant package for graph neural networks M Wang, D Zheng, Z Ye, Q Gan, M Li, X Song, J Zhou, C Ma, L Yu, Y Gai, ... arXiv preprint arXiv:1909.01315, 2019 | 1207 | 2019 |
| The application of two-level attention models in deep convolutional neural network for fine-grained image classification T Xiao, Y Xu, K Yang, J Zhang, Y Peng, Z Zhang Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on, 842-850, 2014 | 1017 | 2014 |
| Error-driven incremental learning in deep convolutional neural network for large-scale image classification T Xiao, J Zhang, K Yang, Y Peng, Z Zhang Proceedings of the 22nd ACM international conference on Multimedia, 177-186, 2014 | 316 | 2014 |
| Visualizing and comparing AlexNet and VGG using deconvolutional layers W Yu, K Yang, Y Bai, T Xiao, H Yao, Y Rui Proceedings of the 33 rd International Conference on Machine Learning, 2016 | 174 | 2016 |
| Scale-invariant convolutional neural networks Y Xu, T Xiao, J Zhang, K Yang, Z Zhang arXiv preprint arXiv:1411.6369, 2014 | 172 | 2014 |
| Bridging the gap to real-world object-centric learning M Seitzer, M Horn, A Zadaianchuk, D Zietlow, T Xiao, CJ Simon-Gabriel, ... The Eleventh International Conference on Learning Representations, 2022 | 75 | 2022 |
| Bag-of-words based deep neural network for image retrieval Y Bai, W Yu, T Xiao, C Xu, K Yang, WY Ma, T Zhao Proceedings of the 22nd ACM international conference on Multimedia, 229-232, 2014 | 52 | 2014 |
| Grin: Generative relation and intention network for multi-agent trajectory prediction L Li, J Yao, L Wenliang, T He, T Xiao, J Yan, D Wipf, Z Zhang Advances in Neural Information Processing Systems 34, 27107-27118, 2021 | 41 | 2021 |
| Layoutdiffuse: Adapting foundational diffusion models for layout-to-image generation J Cheng, X Liang, X Shi, T He, T Xiao, M Li arXiv preprint arXiv:2302.08908, 2023 | 35 | 2023 |
| Learning hierarchical graph neural networks for image clustering Y Xing, T He, T Xiao, Y Wang, Y Xiong, W Xia, D Wipf, Z Zhang, S Soatto Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 33 | 2021 |
| Minerva: A scalable and highly efficient training platform for deep learning M Wang, T Xiao, J Li, J Zhang, C Hong, Z Zhang NIPS Workshop, Distributed Machine Learning and Matrix Computations, 51, 2014 | 32 | 2014 |
| PSS: Progressive sample selection for open-world visual representation learning T Cao, Y Wang, Y Xing, T Xiao, T He, Z Zhang, H Zhou, J Tighe European Conference on Computer Vision, 278-294, 2022 | 6 | 2022 |
| MOOC\一个学生的体验与思考 [J] 肖天骏 中国计算机学会通讯 9 (006), 40-43, 2013 | 6 | 2013 |
| Hallucination of multimodal large language models: A survey Z Bai, P Wang, T Xiao, T He, Z Han, Z Zhang, MZ Shou arXiv preprint arXiv:2404.18930, 2024 | 5 | 2024 |
| Self-supervised amodal video object segmentation J Yao, Y Hong, C Wang, T Xiao, T He, F Locatello, DP Wipf, Y Fu, Z Zhang Advances in Neural Information Processing Systems 35, 6278-6291, 2022 | 5 | 2022 |
| Consistent Video-to-Video Transfer Using Synthetic Dataset J Cheng, T Xiao, T He arXiv preprint arXiv:2311.00213, 2023 | 4 | 2023 |
| Object-centric multiple object tracking Z Zhao, J Wang, M Horn, Y Ding, T He, Z Bai, D Zietlow, CJ Simon-Gabriel, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 4 | 2023 |
| Coarse-to-fine amodal segmentation with shape prior J Gao, X Qian, Y Wang, T Xiao, T He, Z Zhang, Y Fu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 4 | 2023 |
| Rethinking amodal video segmentation from learning supervised signals with object-centric representation K Fan, J Lei, X Qian, M Yu, T Xiao, T He, Z Zhang, Y Fu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 1 | 2023 |
Zheng ZhangProfessor of Computer Science and Engineering, NYU Shanghai; Director, Amazon Shanghai AI Lab在 nyu.edu 的电子邮件经过验证
