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From the 1 of 5 linked papers with an AI index.

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5 papers

cs.CV2026

ReBind: Multi-Reference Video Editing via Structured Instructions with Explicit Reference Relationships

Xinyu Liu, Shihao Li, Weihong Lin +10

The paper introduces ReBind, a framework that uses structured instructions with explicit reference tokens to improve multi‑reference image‑conditioned video editing, enabling preci…

cs.CV2026

AesRM: Improving Video Aesthetics with Expert-Level Feedback

Yujin Han, Yujie Wei, Yefei He +7

Despite rapid advances in photorealistic video generation, real-world applications such as filmmaking require video aesthetics, e.g., harmonious colors and cinematic lighting, beyo…

cs.CV2026

Towards Reason-Informed Video Editing in Unified Models with Self-Reflective Learning

Xinyu Liu, Hangjie Yuan, Yujie Wei +9

Unified video models exhibit strong capabilities in understanding and generation, yet they struggle with reason-informed visual editing even when equipped with powerful internal vi…

cs.CV2025

Content-Adaptive Image Retouching Guided by Attribute-Based Text Representation

Hancheng Zhu, Xinyu Liu, Rui Yao +3

Image retouching has received significant attention due to its ability to achieve high-quality visual content. Existing approaches mainly rely on uniform pixel-wise color mapping a…

cs.CL2025

Turning Internal Gap into Self-Improvement: Promoting the Generation-Understanding Unification in MLLMs

Yujin Han, Hao Chen, Andi Han +5

Although unified MLLMs aim to unify generation and understanding, they are considered to exhibit an internal gap, with understanding outperforming generation. Through large-scale e…