AI RESEARCH
Training-Free Dense Hand Contact Estimation with Multi-Modal Large Language Models
arXiv CS.CV
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ArXi:2605.05886v1 Announce Type: new Dense hand contact estimation requires both high-level semantic understanding and fine-grained geometric reasoning of human interaction to accurately localize contact regions. Recently, multi-modal large language models (MLLMs) have nstrated strong capabilities in understanding visual semantics, enabled by vision-language priors learned from large-scale data. However, leveraging MLLMs for dense hand contact estimation remains underexplored. There are two major challenges in applying MLLMs to dense hand contact estimation.