Opening up Open World Tracking

IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings, pp. 19023–19033

Abstract

Tracking and detecting any object, including ones never-seen-before during model training, is a crucial but elusive capability of autonomous systems. An autonomous agent that is blind to never-seen-before objects poses a safety hazard when operating in the real world - and yet this is how almost all current systems work. One of the main obstacles towards advancing tracking any object is that this task is notoriously difficult to evaluate. A benchmark that would allow us to perform an apples-to-apples comparison of existing efforts is a crucial first step towards advancing this important research field. This paper addresses this evaluation deficit and lays out the landscape and evaluation methodology for detecting and tracking both known and unknown objects in the open-world setting. We propose a new benchmark, TAOOW. Tracking Any Object in an Open World, analyze existing efforts in multi-object tracking, and construct a baseline for this task while highlighting future challenges. We hope to open a new front in multi-object tracking research that will hopefully bring us a step closer to intelligent systems that can operate safely in the real world.

Authors 8

1. Yang Liu

   Technical University of Munich

   Affiliation as printed

   Technical University of Munich,Germany

   Technical University of Munich, Germany

2. Idil Esen Zulfikar Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Germany

   RWTH Aachen University, Germany

3. Jonathon Luiten Aachen

   Carnegie Mellon University · RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Germany

   Carnegie Mellon University, USA

   RWTH Aachen University, Germany

4. Achal Dave

   Carnegie Mellon University

   Affiliation as printed

   Carnegie Mellon University,USA

   Carnegie Mellon University, USA

5. Deva Ramanan

   Carnegie Mellon University

   Affiliation as printed

   Carnegie Mellon University,USA

   Carnegie Mellon University, USA

6. Bastian Leibe Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Germany

   RWTH Aachen University, Germany

7. Aljoša Ošep

   Technical University of Munich · Carnegie Mellon University

   Affiliation as printed

   Technical University of Munich,Germany

   Carnegie Mellon University, USA

   Technical University of Munich, Germany

8. Laura Leal-Taixé

   Technical University of Munich

   Affiliation as printed

   Technical University of Munich,Germany

   Technical University of Munich, Germany