3 accepted papers
Understanding human emotions from images is a challenging yet essential task for vision-language models. While recent efforts have fine-tuned vision-language models to enhance emotional awareness, most approaches rely on global visual representations and fail to capture the nuanced and multi-faceted
We propose a novel method for spatiotemporal multi-camera calibration using freely moving people in multi-view videos. Since calibrating multiple cameras and finding matches across their views are inherently interdependent, performing both in a unified framework poses a significant challenge. We add
We propose a novel camera calibration method for a room-scale multi-view imaging system. Our key idea is to leverage our articulated body movements as a calibration target. We show that a freely moving person provides trajectories of a set of oriented points ( <italic xmlns:mml="http://www.w3.org/19