AFUN predicts task-conditional functional masks and 3D post-contact motion curves from RGB-D and language, trained via a standardized multi-source data pipeline, and reports large gains over baselines on segmentation, contact prediction, and motion tasks.
Develop- ing vision-language-action model from egocentric videos
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The paper surveys four classes of techniques that derive action-related supervision from human videos for VLA robot models and identifies three open challenges in episode structuring, embodiment grounding, and evaluation.
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AFUN: Towards an Affordance Foundation Model for Functionality Understanding
AFUN predicts task-conditional functional masks and 3D post-contact motion curves from RGB-D and language, trained via a standardized multi-source data pipeline, and reports large gains over baselines on segmentation, contact prediction, and motion tasks.
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From Human Videos to Robot Manipulation: A Survey on Scalable Vision-Language-Action Learning with Human-Centric Data
The paper surveys four classes of techniques that derive action-related supervision from human videos for VLA robot models and identifies three open challenges in episode structuring, embodiment grounding, and evaluation.