Motion-aware contrastive video representation learning via foreground-background merging S Ding, M Li, T Yang, R Qian, H Xu, Q Chen, J Wang, H Xiong
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
43 2022 Semi-supervised contrastive learning with similarity co-calibration Y Zhang, X Zhang, J Li, RC Qiu, H Xu, Q Tian
IEEE Transactions on Multimedia 25, 1749-1759, 2022
40 2022 Seed the views: Hierarchical semantic alignment for contrastive representation learning H Xu, X Zhang, H Li, L Xie, W Dai, H Xiong, Q Tian
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (3), 3753-3767, 2022
37 * 2022 Masked autoencoders are robust data augmentors H Xu, S Ding, X Zhang, H Xiong, Q Tian
arXiv preprint arXiv:2206.04846, 2022
23 2022 Fedmax: Enabling a highly-efficient federated learning framework H Xu, J Li, H Xiong, H Lu
2020 IEEE 13th International Conference on Cloud Computing (CLOUD), 426-434, 2020
22 2020 Bag of instances aggregation boosts self-supervised distillation H Xu, J Fang, X Zhang, L Xie, X Wang, W Dai, H Xiong, Q Tian
arXiv preprint arXiv:2107.01691, 2021
19 * 2021 Semantic-aware generation for self-supervised visual representation learning Y Tian, L Xie, X Zhang, J Fang, H Xu, W Huang, J Jiao, Q Tian, Q Ye
arXiv preprint arXiv:2111.13163, 2021
12 2021 -Shot Contrastive Learning of Visual Features With Multiple Instance AugmentationsH Xu, H Xiong, GJ Qi
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 8694 …, 2021
8 2021 Auto-encoding transformations in reparameterized lie groups for unsupervised learning F Lin, H Xu, H Li, H Xiong, GJ Qi
Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 8610-8617, 2021
8 * 2021 Multi-dataset pretraining: A unified model for semantic segmentation B Shi, X Zhang, H Xu, W Dai, J Zou, H Xiong, Q Tian
arXiv preprint arXiv:2106.04121, 2021
6 2021 Flat: Few-shot learning via autoencoding transformation regularizers H Xu, H Xiong, G Qi
arXiv preprint arXiv:1912.12674, 2019
3 2019 Betrayed by Attention: A Simple yet Effective Approach for Self-supervised Video Object Segmentation S Ding, R Qian, H Xu, D Lin, H Xiong
arXiv preprint arXiv:2311.17893, 2023
2023