# Transparent Object Tracking Benchmark

arXiv: https://arxiv.org/abs/2011.10875 · HTML: https://mlsanity.com/paper/2011.10875/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Nov 2020.

## Built on by (most cited first, 19 of 19)

- [Concealed Object Detection](https://mlsanity.com/paper/2102.10274/) (2021)
- [VastTrack: Vast Category Visual Object Tracking](https://mlsanity.com/paper/2403.03493/) (2024)
- [Visual Object Tracking in First Person Vision](https://mlsanity.com/paper/2209.13502/) (2022)
- [Tracking Small and Fast Moving Objects: A Benchmark](https://mlsanity.com/paper/2209.04284/) (2022)
- [360VOT: A New Benchmark Dataset for Omnidirectional Visual Object Tracking](https://mlsanity.com/paper/2307.14630/) (2023)
- [360VOTS: Visual Object Tracking and Segmentation in Omnidirectional Videos](https://mlsanity.com/paper/2404.13953/) (2024)
- [ProBio: A Protocol-guided Multimodal Dataset for Molecular Biology Lab](https://mlsanity.com/paper/2311.00556/) (2023)
- [Tracking Skiers from the Top to the Bottom](https://mlsanity.com/paper/2312.09723/) (2023)
- [Deep Learning in Concealed Dense Prediction](https://mlsanity.com/paper/2504.10979/) (2025)
- [Visual-tactile Fusion for Transparent Object Grasping in Complex Backgrounds](https://mlsanity.com/paper/2211.16693/) (2022)
- [Trans2k: Unlocking the Power of Deep Models for Transparent Object Tracking](https://mlsanity.com/paper/2210.03436/) (2022)
- [A New Dataset and a Distractor-Aware Architecture for Transparent Object Tracking](https://mlsanity.com/paper/2401.03872/) (2024)
- [PlanarTrack: A Large-scale Challenging Benchmark for Planar Object Tracking](https://mlsanity.com/paper/2303.07625/) (2023)
- [Low-Light Object Tracking: A Benchmark](https://mlsanity.com/paper/2408.11463/) (2024)
- [Camouflaged Object Tracking: A Benchmark](https://mlsanity.com/paper/2408.13877/) (2024)
- [Transparent Object Tracking with Enhanced Fusion Module](https://mlsanity.com/paper/2309.06701/) (2023)
- [Tracking Reflected Objects: A Benchmark](https://mlsanity.com/paper/2407.05235/) (2024)
- [DeepSea MOT: A benchmark dataset for multi-object tracking on deep-sea video](https://mlsanity.com/paper/2509.03499/) (2025)
- [Semantic Segmentation of Transparent and Opaque Drinking Glasses with the Help of Zero-shot Learning](https://mlsanity.com/paper/2503.15004/) (2025)

## Abstract (arXiv)

Visual tracking has achieved considerable progress in recent years. However, current research in the field mainly focuses on tracking of opaque objects, while little attention is paid to transparent object tracking. In this paper, we make the first attempt in exploring this problem by proposing a Transparent Object Tracking Benchmark (TOTB). Specifically, TOTB consists of 225 videos (86K frames) from 15 diverse transparent object categories. Each sequence is manually labeled with axis-aligned bounding boxes. To the best of our knowledge, TOTB is the first benchmark dedicated to transparent object tracking. In order to understand how existing trackers perform and to provide comparison for future research on TOTB, we extensively evaluate 25 state-of-the-art tracking algorithms. The evaluation results exhibit that more efforts are needed to improve transparent object tracking. Besides, we observe some nontrivial findings from the evaluation that are discrepant with some common beliefs in opaque object tracking. For example, we find that deeper features are not always good for improvements. Moreover, to encourage future research, we introduce a novel tracker, named TransATOM, which leverages transparency features for tracking and surpasses all 25 evaluated approaches by a large margin. By releasing TOTB, we expect to facilitate future research and application of transparent object tracking in both the academia and industry. The TOTB and evaluation results as well as TransATOM are available at https://hengfan2010.github.io/projects/TOTB.