A method combining head-conditioned local LoRA adaptation and out-of-cone penalty improves gaze reasoning in vision foundation models, yielding state-of-the-art results on GazeFollow and VAT datasets especially for non-salient targets.
An integrated 3d eye-gaze tracking framework for assessing trust in human–robot interaction.ACM Transactions on Human-Robot Interaction, 14(3):1–28, 2025
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Enhancing Gaze Reasoning in Vision Foundation Models for Gaze Following
A method combining head-conditioned local LoRA adaptation and out-of-cone penalty improves gaze reasoning in vision foundation models, yielding state-of-the-art results on GazeFollow and VAT datasets especially for non-salient targets.