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cs.CV2026

VQ-Jarvis: Retrieval-Augmented Video Restoration Agent with Sharp Vision and Fast Thought

Xuanyu Zhang, Weiqi Li, Qunliang Xing +6

Video restoration in real-world scenarios is challenged by heterogeneous degradations, where static architectures and fixed inference pipelines often fail to generalize. Recent age…

cs.CV2026

OARS: Process-Aware Online Alignment for Generative Real-World Image Super-Resolution

Shijie Zhao, Xuanyu Zhang, Bin Chen +8

Aligning generative real-world image super-resolution models with human visual preference is challenging due to the perception--fidelity trade-off and diverse, unknown degradations…

cs.CV2026

Improved Adversarial Diffusion Compression for Real-World Video Super-Resolution

Bin Chen, Weiqi Li, Shijie Zhao +4

While many diffusion models have achieved impressive results in real-world video super-resolution (Real-VSR) by generating rich and realistic details, their reliance on multi-step…

cs.CV2025

UARE: A Unified Vision-Language Model for Image Quality Assessment, Restoration, and Enhancement

Weiqi Li, Xuanyu Zhang, Bin Chen +7

Image quality assessment (IQA) and image restoration are fundamental problems in low-level vision. Although IQA and restoration are closely connected conceptually, most existing wo…

cs.CV2025

TempR1: Improving Temporal Understanding of MLLMs via Temporal-Aware Multi-Task Reinforcement Learning

Tao Wu, Li Yang, Gen Zhan +6

Enhancing the temporal understanding of Multimodal Large Language Models (MLLMs) is essential for advancing long-form video analysis, enabling tasks such as temporal localization,…

cs.CV2025

Reasoning as Representation: Rethinking Visual Reinforcement Learning in Image Quality Assessment

Shijie Zhao, Xuanyu Zhang, Weiqi Li +4

Reasoning-based image quality assessment (IQA) models trained through reinforcement learning (RL) exhibit exceptional generalization, yet the underlying mechanisms and critical fac…