Learning instance-aware object detection using determinantal point processes

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Nuri Kim, Donghoon Lee, Songhwai Oh

Published: 2020, Last Modified: 11 Nov 2025Comput. Vis. Image Underst. 2020EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•The greedy NMS, which has been widely used as a post processing method in object detection, has a poor performance in crowd scenes.•To alleviate this problem, we designed a new trainable post processing method using Determinantal Point Processes.•For training, we proposed an instance-aware detection (ID) loss and sparse score (SS) loss to learn features and scores of objects, respectively.•We demonstrate that the proposed algorithm outperforms baseline detectors for detecting overlapped objects.