3 papers
cs.CV2026
GraftSR: Grafting Authentic Textures for Real-World Image Super-Resolution via Identical-Instance Guidance
Qifan Yu, Haoran Bai, Zongyao He +4
Diffusion-based real-world image super-resolution (SR) achieves impressive perceptual quality but inherently suffers from severe texture hallucination. To overcome this limitation,…
cs.CV2026
SATB-VR: Training Few-Step Video Restoration Diffusion Model using SNR-Aware Trajectory Blending
Haoran Bai, Xiaoxu Chen, Xiaoyu Liu +4
While diffusion models excel in video restoration, their reliance on extensive iterative steps limits efficiency. Conversely, aggressive single-step distillation often compromises…
cs.CV2025
Vivid-VR: Distilling Concepts from Text-to-Video Diffusion Transformer for Photorealistic Video Restoration
Haoran Bai, Xiaoxu Chen, Canqian Yang +3
We present Vivid-VR, a DiT-based generative video restoration method built upon an advanced T2V foundation model, where ControlNet is leveraged to control the generation process, e…