AI RESEARCH
GLANCE: Gaze-Led Attention Network for Compressed Edge-inference
arXiv CS.CV
•
ArXi:2603.15717v1 Announce Type: cross Real-time object detection in AR/VR systems faces critical computational constraints, requiring sub-10\,ms latency within tight power budgets. Inspired by biological foveal vision, we propose a two-stage pipeline that combines differentiable weightless neural networks for ultra-efficient gaze estimation with attention-guided region-of-interest object detection.