Similarity- and Quality-Guided Relation Learning for Joint Detection and Tracking-Reference-Cited by-同舟云学术

Similarity- and Quality-Guided Relation Learning for Joint Detection and Tracking

Author:

Feng Weitao¹^ORCID,Bai Lei²^ORCID,Yao Yongqiang³^ORCID,Gan Weihao³,Wu Wei³^ORCID,Ouyang Wanli⁴^ORCID

Affiliation:

1. School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia

2. Shanghai Artificial Intelligence Laboratory, Shanghai, China

3. SenseTime Group Ltd., Hong Kong, Hong Kong

4. Shanghai Artificial Intelligence Laboratory, School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, Australia

Funder

Australian Research Council

Australian Medical Research Future Fund

CRC-P Smart Material Recovery Facility (SMRF) – Curby Soft Plastics

CRC-P ARIA - Bionic Visual-Spatial Prosthesis for the Blind

Shanghai Artificial Intelligence Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Media Technology,Signal Processing

Link

Reference63 articles.

1. MOTChallenge: Towards a benchmark for multi-target tracking;Leal-Taix,2015

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