NeurIPS 2025poster0 citations

Is This Tracker On? A Benchmark Protocol for Dynamic Tracking

Ilona Demler, Saumya Chauhan, Georgia Gkioxari

Abstract

We introduce ITTO, a challenging new benchmark suite for evaluating and diagnosing the capabilities and limitations of point tracking methods. Our videos are sourced from existing datasets and egocentric real-world recordings, with high-quality human annotations collected through a multi-stage pipeline. ITTO captures the motion complexity, occlusion patterns, and object diversity characteristic of real-world scenes -- factors that are largely absent in current benchmarks. We conduct a rigorous analysis of state-of-the-art tracking methods on ITTO, breaking down performance along key axes of motion complexity. Our findings reveal that existing trackers struggle with these challenges, particularly in re-identifying points after occlusion, highlighting critical failure modes. These results point to the need for new modeling approaches tailored to real-world dynamics. We envision ITTO as a foundation testbed for advancing point tracking and guiding the development of more robust tracking algorithms.

trackingtracking-any-pointoptical flow
BibTeX
@inproceedings{
demler2025is,
title={Is This Tracker On? A Benchmark Protocol for Dynamic Tracking},
author={Ilona Demler and Saumya Chauhan and Georgia Gkioxari},
booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
year={2025},
url={https://openreview.net/forum?id=ZXiOUfaWQT}
}