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Showing 2026 · cs.CVShow all

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cs.CV2026

ACE-Ego-Hand: Repurposing Video Diffusion Models for Occlusion-Robust Egocentric 3D Hand Motion Recovery

Yufei Liu, Xixi Wang, Hao Li +8

Egocentric video offers scalable manipulation data for embodied AI, yet recovering metric 3D hand trajectories remains challenging due to severe object occlusion and frequent out-o…

cs.CV2026

HarnessEval-W: Agentifying the Evaluation of Visual Worlds

Weiliang Chen, Haowen Sun, Jun Gao +40

A benchmark should deliver more than a scalar score: what makes an evaluation trustworthy is the reasoning that justifies the score. This is especially critical for world models, w…

cs.CV2026

S-Agent: Spatial Tool-Use Elicits Reasoning for Spatial Intelligence

Yalun Dai, Hao Li, Shulin Tian +8

Real-world spatial intelligence requires reasoning over a continuous and evolving 3D world, yet existing VLMs and tool-augmented agents largely remain tied to static, stateless inf…

cs.CV2026

Apple-: Benchmarking Thinking with Video Towards Law-Grounded Physical Intelligence

Runmao Yao, Kairui Hu, Yukang Cao +11

Modern video generation models are increasingly hailed as emerging world models with an internalized grasp of physical law. Yet existing benchmarks largely evaluate physical plausi…

cs.CV2026

SpatialBench: Is Your Spatial Foundation Model an All-Round Player?

Haosong Peng, Hao Li, Jiaqi Chen +10

While spatial foundation models have demonstrated impressive performance on standard datasets, a critical question remains: are they truly all-round players capable of generalizing…

cs.CV2026

Rethinking VLM Representation for VLA Initialization

Weifeng Lin, Siyuan Huang, Hao Li +5

Vision-Language-Action (VLA) models widely adopt pretrained Vision-Language Models (VLMs) as policy backbones, yet it remains unclear what kind of pretrained VLM representation is…