Work

HOOT: Heavy Occlusions in Object Tracking Benchmark

Year: 2023

Type: conference-paper

Source: IEEE Winter Conference on Applications of Computer Vision

DOI: 10.1109/wacv56688.2023.00481

Authors: Gozde Sahin, Laurent Itti

Institution: University of Southern California

Language: English

Topic: Video Surveillance and Tracking Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funder: Army Research Office

OpenAlex ID: W4319300589

FWCI: 0.509

Cites: 42

Cited by: 5

Related to: 10