PCIE_Interaction Solution for Ego4D Social Interaction Challenge
Journal:
arXiv
Published Date:
May 30, 2025
Abstract
This report presents our team's PCIE_Interaction solution for the Ego4D
Social Interaction Challenge at CVPR 2025, addressing both Looking At Me (LAM)
and Talking To Me (TTM) tasks. The challenge requires accurate detection of
social interactions between subjects and the camera wearer, with LAM relying
exclusively on face crop sequences and TTM combining speaker face crops with
synchronized audio segments. In the LAM track, we employ face quality
enhancement and ensemble methods. For the TTM task, we extend visual
interaction analysis by fusing audio and visual cues, weighted by a visual
quality score. Our approach achieved 0.81 and 0.71 mean average precision (mAP)
on the LAM and TTM challenges leader board. Code is available at
https://github.com/KanokphanL/PCIE_Ego4D_Social_Interaction
