Pedestrian Detection Using MB-CSP Model and Boosted Identity Aware Non-Maximum Suppression
Author:
Affiliation:
1. Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada
Funder
Natural Sciences and Engineering Research Council (NSERC) of Canada
Western Canada Research Grid
Compute Canada
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/9972869/09857630.pdf?arnumber=9857630
Reference34 articles.
1. Occlusion-Aware R-CNN: Detecting Pedestrians in a Crowd
2. Coupled Network for Robust Pedestrian Detection With Gated Multi-Layer Feature Extraction and Deformable Occlusion Handling
3. Discriminative Feature Transformation for Occluded Pedestrian Detection
4. CircleNet: Reciprocating Feature Adaptation for Robust Pedestrian Detection
5. Learning Efficient Single-Stage Pedestrian Detectors by Asymptotic Localization Fitting
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