| ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation L Yang, W Zhuo, L Qi, Y Shi, Y Gao IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 239 | 2022 |
| Mining Latent Classes for Few-shot Segmentation L Yang, W Zhuo, L Qi, Y Shi, Y Gao IEEE International Conference on Computer Vision (ICCV) (Oral), 2021 | 109 | 2021 |
| Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation L Yang, L Qi, L Feng, W Zhang, Y Shi IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023 | 99 | 2023 |
| Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data L Yang, B Kang, Z Huang, X Xu, J Feng, H Zhao IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024 | 27 | 2024 |
| FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models L Yang, X Xu, B Kang, Y Shi, H Zhao Conference on Neural Information Processing Systems (NeurIPS), 2023 | 9 | 2023 |
| Augmentation Matters: A Simple-yet-Effective Approach to Semi-supervised Semantic Segmentation Z Zhao, L Yang, S Long, J Pi, L Zhou, J Wang IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023 | 8 | 2023 |
| Diverse Cotraining Makes Strong Semi-Supervised Segmentor Y Li, X Wang, L Yang, L Feng, W Zhang, Y Gao IEEE International Conference on Computer Vision (ICCV), 2023 | 5 | 2023 |
| Shrinking Class Space for Enhanced Certainty in Semi-Supervised Learning L Yang, Z Zhao, L Qi, Y Qiao, Y Shi, H Zhao IEEE International Conference on Computer Vision (ICCV), 2023 | 5 | 2023 |
Yinghuan Shi（史颖欢）Nanjing UniversityVerified email at nju.edu.cn
