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cs.CV2026

OmniVR: Audio-Video Conditional Generation for Archival Footage Restoration

Xin Lu, Zihao Fan, Mingchen Zhong +4

Archival footage often suffers from coupled visual and acoustic degradations, yet most restoration systems process the two modalities separately. To address this problem, we presen…

cs.CV2026

Ultra Flash: Scaling Real-Time Streaming Video Generation to High Resolutions

Xin Lu, Luxury, Jie Huang +27

While recent autoregressive video diffusion models achieve remarkable streaming quality, they remain confined to low resolutions (e.g., 480P), leaving efficient, scalable, real-tim…

cs.CV2026

IR-Flow: Bridging Discriminative and Generative Image Restoration via Rectified Flow

Zihao Fan, Xin Lu, Jie Xiao +3

In image restoration, single-step discriminative mappings often lack fine details via expectation learning, whereas generative paradigms suffer from inefficient multi-step sampling…

cs.CV2026

Bird-SR: Bidirectional Reward-Guided Diffusion for Real-World Image Super-Resolution

Zihao Fan, Xin Lu, Yidi Liu +4

Powered by multimodal text-to-image priors, diffusion-based super-resolution excels at synthesizing intricate details; however, models trained on synthetic low-resolution (LR) and…

cs.CV2025

FinPercep-RM: A Fine-grained Reward Model and Co-evolutionary Curriculum for RL-based Real-world Super-Resolution

Yidi Liu, Zihao Fan, Jie Huang +6

Reinforcement Learning with Human Feedback (RLHF) has proven effective in image generation field guided by reward models to align human preferences. Motivated by this, adapting RLH…

cs.CV2025

Elucidating and Endowing the Diffusion Training Paradigm for General Image Restoration

Xin Lu, Xueyang Fu, Jie Xiao +3

While diffusion models demonstrate strong generative capabilities in image restoration (IR) tasks, their complex architectures and iterative processes limit their practical applica…

cs.CV2025

NTIRE 2025 Image Shadow Removal Challenge Report

Florin-Alexandru Vasluianu, Tim Seizinger, Zhuyun Zhou +79

This work examines the findings of the NTIRE 2025 Shadow Removal Challenge. A total of 306 participants have registered, with 17 teams successfully submitting their solutions durin…