# Opening up Open-World Tracking

Source: [Opening up Open-World Tracking](<https://www.sota2.com/research/paper/68fa6c1d1e209131cea324ff>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T00:04:48.767Z

Authors: Yang Liu, Idil Esen Zulfikar, Jonathon Luiten, Achal Dave, Deva Ramanan, Bastian Leibe, Aljo\\v{s}a O\\v{s}ep, Laura Leal-Taix\\'e

Published: 2021-04-22T17:58:15.000Z

## 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, TAO-OW: 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. https://openworldtracking.github.io/

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Open-world tracking on BURST (test)](<https://www.sota2.com/research/sota/open-world-tracking-on-burst-test.md>): Open-world tracking; BURST (test); Unseen Performance: 38.3.

- [Open-World Video Segmentation on BURST (test)](<https://www.sota2.com/research/sota/open-world-video-segmentation-on-burst-test.md>): Open-World Video Segmentation; BURST (test); OWTA All: 56.

- [Open-World Video Segmentation on BURST (val)](<https://www.sota2.com/research/sota/open-world-video-segmentation-on-burst-val.md>): Open-World Video Segmentation; BURST (val); OWTA (All): 55.8.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2104.11221>)

[PDF](<https://arxiv.org/pdf/2104.11221.pdf>)