Learning by analogy: Reliable supervision from transformations for unsupervised optical flow estimation L Liu, J Zhang, R He, Y Liu, Y Wang, Y Tai, D Luo, C Wang, J Li, F Huang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 175 | 2020 |
Is synthetic data from generative models ready for image recognition? R He, S Sun, X Yu, C Xue, W Zhang, P Torr, S Bai, X Qi arXiv preprint arXiv:2210.07574, 2022 | 163 | 2022 |
Re-distributing biased pseudo labels for semi-supervised semantic segmentation: A baseline investigation R He, J Yang, X Qi Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 123 | 2021 |
Knowledge distillation as efficient pre-training: Faster convergence, higher data-efficiency, and better transferability R He, S Sun, J Yang, S Bai, X Qi Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 28 | 2022 |
LUMix: Improving mixup by better modelling label uncertainty S Sun, JN Chen, R He, A Yuille, P Torr, S Bai arXiv preprint arXiv:2211.15846, 2022 | 4 | 2022 |
Vertical Layering of Quantized Neural Networks for Heterogeneous Inference H Wu, R He, H Tan, X Qi, K Huang IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 1 | 2023 |
Debiasing Text-to-Image Diffusion Models R He, C Xue, H Tan, W Zhang, Y Yu, S Bai, X Qi arXiv preprint arXiv:2402.14577, 2024 | | 2024 |