collaborators

5 papers

cs.CV2026

OmniEdit-Bench: A Comprehensive Benchmark for Instruction-based Video Editing

Chenxuan Miao, Yutong Feng, Yi Lu +6

Instruction-based video editing (IVE) is an emerging field with broad applications, yet evaluating editing models remains challenging. Existing benchmarks suffer from two major lim…

cs.CV2025

ROSE: Remove Objects with Side Effects in Videos

Chenxuan Miao, Yutong Feng, Jianshu Zeng +7

Video object removal has achieved advanced performance due to the recent success of video generative models. However, when addressing the side effects of objects, e.g., their shado…

cs.CV2025

OmniTry: Virtual Try-On Anything without Masks

Yutong Feng, Linlin Zhang, Hengyuan Cao +5

Virtual Try-ON (VTON) is a practical and widely-applied task, for which most of existing works focus on clothes. This paper presents OmniTry, a unified framework that extends VTON…

cs.CV2025

Lumen: Consistent Video Relighting and Harmonious Background Replacement with Video Generative Models

Jianshu Zeng, Yuxuan Liu, Yutong Feng +6

Video relighting is a challenging yet valuable task, aiming to replace the background in videos while correspondingly adjusting the lighting in the foreground with harmonious blend…

cs.CV2025

Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis

Hengyuan Cao, Yutong Feng, Biao Gong +4

Video generative models can be regarded as world simulators due to their ability to capture dynamic, continuous changes inherent in real-world environments. These models integrate…