Notice

Hit 217
Subject [ICCV 2021] Robust Small-scale Pedestrian Detection with Cued Recall via Memory Learning (by Jung Uk Kim and Sungjune Park) is accepted in ICCV 2021
Date 2021-07-23
Title: Robust Small-scale Pedestrian Detection with Cued Recall via Memory Learning
Authors: Jung Uk Kim*, Sungjune Park*, and Yong Man Ro (*: equally contributed)
 
Although the visual appearances of small-scale objects are not well observed, humans can recognize them by associating the visual cues of small objects from their memorized appearance. It is called cued recall. In this paper, motivated by the memory process of humans, we introduce a novel pedestrian detection framework that imitates cued recall in detecting the small-scale pedestrians. We propose a large-scale embedding learning with the large-scale pedestrian recalling memory (LPR Memory). The purpose of the proposed large-scale pedestrian embedding learning is to memorize and recall the large-scale pedestrian appearance via the LPR Memory. To this end, we employ the large-scale pedestrian exemplar set, so that, the LPR Memory can recall the information of the large-scale pedestrians from the small-scale pedestrians. Comprehensive quantitative and qualitative experimental results validate the effectiveness of the proposed framework with the LPR Memory.