Paper ID | IFS-1.2 | ||
Paper Title | ATTENTION-BASED PARTIAL FACE RECOGNITION | ||
Authors | Stefan Hörmann, Zeyuan Zhang, Martin Knoche, Torben Teepe, Gerhard Rigoll, Technical University of Munich, Germany | ||
Session | IFS-1: Biometrics | ||
Location | Area K | ||
Session Time: | Monday, 20 September, 13:30 - 15:00 | ||
Presentation Time: | Monday, 20 September, 13:30 - 15:00 | ||
Presentation | Poster | ||
Topic | Information Forensics and Security: Biometrics | ||
IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
Abstract | Photos of faces captured in unconstrained environments, such as large crowds, still constitute challenges for current face recognition approaches as often faces are occluded by objects or people in the foreground. However, few studies have addressed the task of recognizing partial faces. In this paper, we propose a novel approach to partial face recognition capable of recognizing faces with different occluded areas. We achieve this by combining attentional pooling of a ResNet's intermediate feature maps with a separate aggregation module. We further adapt common losses to partial faces in order to ensure that the attention maps are diverse and handle occluded parts. Our thorough analysis demonstrates that we outperform all baselines under multiple benchmark protocols, including naturally and synthetically occluded partial faces. This suggests that our method successfully focuses on the relevant parts of the occluded face. |