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cs.CV2026

EgoTools: Towards Tool-Centric Reasoning in Real-World Egocentric Videos

Shulin Tian, Junsu Kim, Shuai Liu +17

Real-world embodied tasks, from everyday activities to professional procedures, require agents to act under physical constraints while tracking evolving object and task states. Too…

cs.CV2026

V-Rubrics: Visual Faithfulness via Rubric-Based Reinforcement Learning

Shulin Tian, Minglun Li, Yuhao Dong +6

Vision-language models can produce fluent answers that are insufficiently grounded in the visual evidence: a single unsupported object, chart value, or intermediate inference can u…

cs.CV2026

A Simple Baseline for Streaming Video Understanding

Yujiao Shen, Shulin Tian, Jingkang Yang +1

Recent streaming video understanding methods increasingly rely on complex memory mechanisms to handle long video streams. We challenge this trend with a simple finding: a sliding-w…

cs.CV2025

UNO: Unifying One-stage Video Scene Graph Generation via Object-Centric Visual Representation Learning

Huy Le, Nhat Chung, Tung Kieu +2

Video Scene Graph Generation (VidSGG) aims to represent dynamic visual content by detecting objects and modeling their temporal interactions as structured graphs. Prior studies typ…

cs.CV2025

Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scene

Shengqiong Wu, Hao Fei, Jingkang Yang +4

The latest emerged 4D Panoptic Scene Graph (4D-PSG) provides an advanced-ever representation for comprehensively modeling the dynamic 4D visual real world. Unfortunately, current p…