The VOT challenges provide the visual tracking community with a precisely defined and repeatable way of comparing short-term trackers as well as a common platform for discussing the evaluation and advancements made in the field of visual tracking.

The goal of the challenges is to build up a repository of considerable benchmarks and to organize workshops or similar events in order to push forward research in visual tracking.


Announcing VOTS2024!


We are pleased to announce that the activities for VOTS2024 are well underway! The following three challenges are planned:

  • VOTS2024 challenge - Continuation of the VOTS2023 challenge. The task is to track one or more general targets over short-term or long-term sequences by segmentation. The VOTS evaluation server will be used for submission.
  • VOTSt2024 challenge - A new challenge this year considers general objects undergoing a topological transformation, such as vegetables cut into pieces, machines disassembled, etc. It will be based on the recent VOST dataset and will use the same evaluation methodology as VOTS2024. The VOTS evaluation server will be used for submission.
  • VOTS-GenArt2024 challenge - Continuation of the VOTS-GenArt2023 challenge aimed at showcasing creativity and artistic flair of the tracking community in the era of generative computer vision. The task is to generate VOTS-related images or short video clips using generative models. Submissions on the VOT X/Twitter channel.

Important dates

  • 13th of May, 2024 - All challenges open
  • 23rd of June, 2024 - VOTS2024 & VOTSt2024 results submission deadline
  • 13th of July, 2024 - VOTS2024 & VOTSt2024 winners announcement
  • 8th of August, 2024 - VOTS-GenArt2024 closes
  • 30th of September, 2024 - VOTS2024 workshop (pending acceptance of the WS proposal)


Citing VOT Challenge

When using any of VOT benchmarks in your paper, please cite the VOT journal paper as well as the relevant VOT workshop paper describing the relevant benchmark.

@article {VOT_TPAMI, author = {Matej Kristan and Jiri Matas and Ale\v{s} Leonardis and Tomas Vojir and Roman Pflugfelder and Gustavo Fernandez and Georg Nebehay and Fatih Porikli and Luka \v{C}ehovin}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, title={A Novel Performance Evaluation Methodology for Single-Target Trackers}, year={2016}, month={Nov}, volume={38}, number={11}, pages={2137-2155}, doi={10.1109/TPAMI.2016.2516982}, ISSN={0162-8828} }