Request to add several recent works to the Image Representation Learning section. They employ generative feedback to perform self-supervised learning for image representation.
2025
- Reconstructive Visual Instruction Tuning
[pdf]
[code]
- Haochen Wang, Anlin Zheng, Yucheng Zhao, Tiancai Wang, Zheng Ge, Xiangyu Zhang, Zhaoxiang Zhang. ICLR 2025
- Diffusion Feedback Helps CLIP See Better
[pdf]
[code]
- Wenxuan Wang, Quan Sun, Fan Zhang, Yepeng Tang, Jing Liu, Xinlong Wang. ICLR 2025
- GenHancer: Imperfect Generative Models are Secretly Strong Vision-Centric Enhancers
[pdf]
[code]
- Shijie Ma, Yuying Ge, Teng Wang, Yuxin Guo, Yixiao Ge, Ying Shan. ICCV 2025
- un$^2$CLIP: Improving CLIP's Visual Detail Capturing Ability via Inverting unCLIP
[pdf]
[code]
- Yinqi Li, Jiahe Zhao, Hong Chang, Ruibing Hou, Shiguang Shan, Xilin Chen. NeurIPS 2025
2026
- Guiding Diffusion-based Reconstruction with Contrastive Signals for Balanced Visual Representation
[pdf]
[code]
- Boyu Han, Qianqian Xu, Shilong Bao, Zhiyong Yang, Ruochen Cui, Xilin Zhao, Qingming Huang. CVPR 2026
Request to add several recent works to the Image Representation Learning section. They employ generative feedback to perform self-supervised learning for image representation.
2025
[pdf]
[code]
[pdf]
[code]
[pdf]
[code]
[pdf]
[code]
2026
[pdf]
[code]