collaborators

8 papers

cs.CV2026

Evidence-Driven Dynamic Visual Selector for Efficient Long Video Understanding

Bo Zhang, Wenxin Wang, Feng Chen +4

Recent advancements in MLLM-based long-form video understanding have mitigated inference-time computational cost and limited context lengths by selecting query-relevant frames. How…

cs.CV2026

Agentic Collaborative Cognition for Zero-Shot 3D Understanding

Wenxin Wang, Bo Zhang, Feng Chen +4

Recent advancements have explored agentic zero-shot 3D understanding by reformulating it as video keyframe understanding with Multimodal Large Language Models (MLLMs). However, exi…

cs.CV2026

PolicyTrim: Boosting Intrinsic Policy Efficiency of Vision-Language-Action Models

Xianghui Wang, Feng Chen, Wenbo Zhang +4

Vision-Language-Action (VLA) models provide a unified paradigm for robotic manipulation, yet their real-world deployment is often bottlenecked by execution efficiency. While existi…

cs.RO2026

PhysAgent: Automating Physics-Based 4D Synthesis via Trajectory-Grounded Multi-Agent Feedback

Chunji Lv, Jiaxi Ye, Yuchen Jiang +2

Achieving fully automated, physically plausible 3D motion synthesis is a core objective in graphics and generative AI. However, configuring complex environmental force fields still…

cs.CV2026

Training-free Motion Factorization for Compositional Video Generation

Zixuan Wang, Ziqin Zhou, Feng Chen +4

Compositional video generation aims to synthesize multiple instances with diverse appearance and motion. However, current approaches mainly focus on binding semantics, neglecting t…

cs.CV2026

PhysGM: Large Physical Gaussian Model for Feed-Forward 4D Synthesis

Chunji Lv, Zequn Chen, Donglin Di +5

Despite advances in physics-based 3D motion synthesis, current methods face key limitations: reliance on pre-reconstructed 3D Gaussian Splatting (3DGS) built from dense multi-view…