Cas-RetinaNet improves RetinaNet by 2 AP on MS COCO by training cascade stages on rising IoU thresholds and adding a Feature Consistency Module to align classification confidence with localization accuracy.
WIDER Face and Pedestrian Challenge 2018: Methods and Results
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abstract
This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian. The challenge focuses on the problem of precise localization of human faces and bodies, and accurate association of identities. It comprises of three tracks: (i) WIDER Face which aims at soliciting new approaches to advance the state-of-the-art in face detection, (ii) WIDER Pedestrian which aims to find effective and efficient approaches to address the problem of pedestrian detection in unconstrained environments, and (iii) WIDER Person Search which presents an exciting challenge of searching persons across 192 movies. In total, 73 teams made valid submissions to the challenge tracks. We summarize the winning solutions for all three tracks. and present discussions on open problems and potential research directions in these topics.
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cs.CV 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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Cascade RetinaNet: Maintaining Consistency for Single-Stage Object Detection
Cas-RetinaNet improves RetinaNet by 2 AP on MS COCO by training cascade stages on rising IoU thresholds and adding a Feature Consistency Module to align classification confidence with localization accuracy.