5 papers
From Synthesis to Removal: Physics-Grounded Reflection Simulation and Diffusion-Based Video Dereflection
Zepeng Wang, Jiagao Hu, Fuhao Li +3
Videos captured through glass often contain reflections that degrade visual quality and interfere with downstream vision tasks. Although single-image reflection removal has been ex…
PROVE: A Perceptual RemOVal cohErence Benchmark for Visual Media
Fuhao Li, Shaofeng You, Jiagao Hu +6
Evaluating object removal in images and videos remains challenging because the task is inherently one-to-many, yet existing metrics frequently disagree with human perception. Full-…
CapVector: Learning Transferable Capability Vectors in Parametric Space for Vision-Language-Action Models
Wenxuan Song, Han Zhao, Fuhao Li +7
This paper proposes a novel approach to address the challenge that pretrained VLA models often fail to effectively improve performance and reduce adaptation costs during standard s…
From Ideal to Real: Stable Video Object Removal under Imperfect Conditions
Jiagao Hu, Yuxuan Chen, Fuhao Li +4
Removing objects from videos remains difficult in the presence of real-world imperfections such as shadows, abrupt motion, and defective masks. Existing diffusion-based video inpai…
AutoAWG: Adverse Weather Generation with Adaptive Multi-Controls for Automotive Videos
Jiagao Hu, Daiguo Zhou, Danzhen Fu +6
Perception robustness under adverse weather remains a critical challenge for autonomous driving, with the core bottleneck being the scarcity of real-world video data in adverse wea…