Gaze-VLM:Bridging Gaze and VLMs through Attention Regularization for Egocentric Understanding

📰 ArXiv cs.AI

Gaze-VLM framework uses attention regularization to bridge gaze and visual language models for egocentric understanding

advanced Published 25 Mar 2026

Action Steps

Propose a gaze-regularized framework to enhance VLMs
Use attention regularization to bridge gaze and visual inputs
Apply the framework to fine-grained future event prediction and current activity understanding tasks
Evaluate the performance of the Gaze-VLM framework against prior approaches

Who Needs to Know This

AI engineers and researchers working on egocentric understanding tasks can benefit from this framework to improve fine-grained future event prediction and current activity understanding

Key Insight

💡 Attention regularization can effectively integrate gaze cues into VLMs for improved egocentric understanding