collaborators

10 papers

cs.CV2026

Superman: Unifying Skeleton and Vision for Human Motion Perception and Generation

Xinshun Wang, Peiming Li, Ziyi Wang +5

Human motion analysis tasks, such as temporal 3D pose estimation, motion prediction, and motion in-betweening, play an essential role in computer vision. However, current paradigms…

cs.RO2026

Eval-Actions: Fine-Grained Execution Quality Evaluation for Robotic Manipulation

Mengyuan Liu, Juyi Sheng, Peiming Li +4

Although Vision--Action (VA) and Vision--Language--Action (VLA) policies have advanced robotic manipulation, their evaluation remains dominated by binary success rates, which obscu…

cs.LG2026

AcceRL: A Distributed Asynchronous Reinforcement Learning and World Model Framework for Vision-Language-Action Models

Chengxuan Lu, Shukuan Wang, Yanjie Li +10

Reinforcement learning (RL) for large-scale Vision-Language-Action (VLA) models is severely bottlenecked by synchronization barriers and the high cost of environment data acquisiti…

cs.CV2026

Lens Privacy Sealing: A New Benchmark and Method for Physical Privacy-Preserving Action Recognition

Mengyuan Liu, Ziyi Wang, Peiming Li +1

RGB camera-based surveillance systems enable human action recognition for public safety and healthcare, yet raise serious privacy concerns. Existing methods rely on post-capture al…

cs.CV2026

Universal Skeleton Understanding via Differentiable Rendering and MLLMs

Ziyi Wang, Peiming Li, Xinshun Wang +3

Multimodal large language models (MLLMs) exhibit strong visual-language reasoning, yet cannot process structured, non-visual data such as human skeletons. Existing methods either c…

cs.CV2026

GenVideoLens: Where LVLMs Fall Short in AI-Generated Video Detection?

Yueying Zou, Pei Pei Li, Zekun Li +4

In recent years, AI-generated videos have become increasingly realistic and sophisticated. Meanwhile, Large Vision-Language Models (LVLMs) have shown strong potential for detecting…