most citedOpen-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

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cs.CV2026

SlotVTG: Object-Centric Adapter for Generalizable Video Temporal Grounding

Jiwook Han, Geo Ahn, Youngrae Kim +1

Multimodal Large Language Models (MLLMs) have shown strong performance on Video Temporal Grounding (VTG). However, their coarse recognition capabilities are insufficient for fine-g…

cs.CV2026

Do Vision Language Models Understand Human Engagement in Games?

Ziyi Wang, Qizan Guo, Rishitosh Singh +1

Inferring human engagement from gameplay video is important for game design and player-experience research, yet it remains unclear whether vision--language models (VLMs) can infer…

cs.CV2026

UniMotion: A Unified Framework for Motion-Text-Vision Understanding and Generation

Ziyi Wang, Xinshun Wang, Shuang Chen +2

We present UniMotion, to our knowledge the first unified framework for simultaneous understanding and generation of human motion, natural language, and RGB images within a single a…

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

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.CV2025

UST-SSM: Unified Spatio-Temporal State Space Models for Point Cloud Video Modeling

Peiming Li, Ziyi Wang, Yulin Yuan +4

Point cloud videos capture dynamic 3D motion while reducing the effects of lighting and viewpoint variations, making them highly effective for recognizing subtle and continuous hum…

cs.CV2025

Recognizing Actions from Robotic View for Natural Human-Robot Interaction

Ziyi Wang, Peiming Li, Hong Liu +5

Natural Human-Robot Interaction (N-HRI) requires robots to recognize human actions at varying distances and states, regardless of whether the robot itself is in motion or stationar…