2 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
Semi-Supervised Video Desnowing Network via Temporal Decoupling Experts and Distribution-Driven Contrastive Regularization
Hongtao Wu, Yijun Yang, Angelica I Aviles-Rivero +4
Snow degradations present formidable challenges to the advancement of computer vision tasks by the undesirable corruption in outdoor scenarios. While current deep learning-based de…
RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models
Haoyu Chen, Wenbo Li, Jinjin Gu +7
Natural images captured by mobile devices often suffer from multiple types of degradation, such as noise, blur, and low light. Traditional image restoration methods require manual…
UltraPixel: Advancing Ultra-High-Resolution Image Synthesis to New Peaks
Jingjing Ren, Wenbo Li, Haoyu Chen +6
Ultra-high-resolution image generation poses great challenges, such as increased semantic planning complexity and detail synthesis difficulties, alongside substantial training reso…
Towards Realistic Data Generation for Real-World Super-Resolution
Long Peng, Wenbo Li, Renjing Pei +5
Existing image super-resolution (SR) techniques often fail to generalize effectively in complex real-world settings due to the significant divergence between training data and prac…
Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning
Haoyu Chen, Wenbo Li, Jinjin Gu +6
For image super-resolution (SR), bridging the gap between the performance on synthetic datasets and real-world degradation scenarios remains a challenge. This work introduces a nov…