# 3D-ZeF: A 3D Zebrafish Tracking Benchmark Dataset

arXiv: https://arxiv.org/abs/2006.08466 · HTML: https://mlsanity.com/paper/2006.08466/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Jun 2020.

## Built on by (most cited first, 24 of 24)

- [SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos](https://mlsanity.com/paper/2204.06918/) (2022)
- [The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions](https://mlsanity.com/paper/2104.02710/) (2021)
- [Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?](https://mlsanity.com/paper/2210.07681/) (2022)
- [The Caltech Fish Counting Dataset: A Benchmark for Multiple-Object Tracking and Counting](https://mlsanity.com/paper/2207.09295/) (2022)
- [ChimpACT: A Longitudinal Dataset for Understanding Chimpanzee Behaviors](https://mlsanity.com/paper/2310.16447/) (2023)
- [How Severe is Benchmark-Sensitivity in Video Self-Supervised Learning?](https://mlsanity.com/paper/2203.14221/) (2022)
- [WebUOT-1M: Advancing Deep Underwater Object Tracking with A Million-Scale Benchmark](https://mlsanity.com/paper/2405.19818/) (2024)
- [In Pursuit of Many: A Review of Modern Multiple Object Tracking Systems](https://mlsanity.com/paper/2209.04796/) (2022)
- [3D-MuPPET: 3D Multi-Pigeon Pose Estimation and Tracking](https://mlsanity.com/paper/2308.15316/) (2023)
- [BrackishMOT: The Brackish Multi-Object Tracking Dataset](https://mlsanity.com/paper/2302.10645/) (2023)
- [The SA-FARI Dataset: Segment Anything in Footage of Animals for Recognition and Identification](https://mlsanity.com/paper/2511.15622/) (2025)
- [AlphaChimp: Tracking and Behavior Recognition of Chimpanzees](https://mlsanity.com/paper/2410.17136/) (2024)
- [Enhancing Thermal MOT: A Novel Box Association Method Leveraging Thermal Identity and Motion Similarity](https://mlsanity.com/paper/2411.12943/) (2024)
- [SEVERE++: Evaluating Benchmark Sensitivity in Generalization of Video Representation Learning](https://mlsanity.com/paper/2504.05706/) (2025)
- [MOTCOM: The Multi-Object Tracking Dataset Complexity Metric](https://mlsanity.com/paper/2207.10031/) (2022)
- [When Trackers Date Fish: A Benchmark and Framework for Underwater Multiple Fish Tracking](https://mlsanity.com/paper/2507.06400/) (2025)
- [Overcoming the Domain Gap in Neural Action Representations](https://mlsanity.com/paper/2112.01176/) (2021)
- [Reliable Multi-Object Tracking in the Presence of Unreliable Detections](https://mlsanity.com/paper/2112.08345/) (2021)
- [Mouse Lockbox Dataset: Behavior Recognition for Mice Solving Lockboxes](https://mlsanity.com/paper/2505.15408/) (2025)
- [Head Anchor Enhanced Detection and Association for Crowded Pedestrian Tracking](https://mlsanity.com/paper/2508.05514/) (2025)
- [Reference-based Category Discovery: Unsupervised Object Detection with Category Awareness](https://mlsanity.com/paper/2605.04606/) (2026)
- [Teach a Molmo2Fish: Towards interactive fish tracking with natural language guidance](https://mlsanity.com/paper/2608.18602/) (2026)
- [TrackFish3D: Self-Supervised 3D Tracking of Schooling Fish from Multi-view Videos](https://mlsanity.com/paper/2609.38347/) (2026)
- [FiVOS: A Fish Segmentation Algorithm Based on Interactive Video Object Segmentation and Filter Enhancement](https://mlsanity.com/paper/2610.01480/) (2026)

## Abstract (arXiv)

In this work we present a novel publicly available stereo based 3D RGB dataset for multi-object zebrafish tracking, called 3D-ZeF. Zebrafish is an increasingly popular model organism used for studying neurological disorders, drug addiction, and more. Behavioral analysis is often a critical part of such research. However, visual similarity, occlusion, and erratic movement of the zebrafish makes robust 3D tracking a challenging and unsolved problem. The proposed dataset consists of eight sequences with a duration between 15-120 seconds and 1-10 free moving zebrafish. The videos have been annotated with a total of 86,400 points and bounding boxes. Furthermore, we present a complexity score and a novel open-source modular baseline system for 3D tracking of zebrafish. The performance of the system is measured with respect to two detectors: a naive approach and a Faster R-CNN based fish head detector. The system reaches a MOTA of up to 77.6%. Links to the code and dataset is available at the project page https://vap.aau.dk/3d-zef