Datasets › FISHTRAC

FISHTRAC (Nguyen Minh Khiem)

Introduced by Travis Mandel et al. in Reliable Multi-Object Tracking in the Presence of Unreliable Detections1 Nov 2022 archive 2025-07-28

A dataset of real-world underwater videos annotated with multi-object tracking labels. The data was collected of the coast of the Big Island of Hawaii and the primary goal is to help scientists studying fish behavior, with the goal of conserving rare and beautiful fish species.

Features: * Real-world video collected primarily by divers : Results in complex camera motion and complex background effects (coral), which poses a challenge for many tracking systems. * Limited training data: Only 3 videos reserved for training, the other 11 are reserved for testing. This allows one to examine how approaches cope with little training data. * Provided deep detections: Unfiltered deep detections are provided from RetinaNet. These detections are reasonable but imperfect, allowing one to examine how to cope with unfiltered predictions. * Complete labels: Every frame is annotated, and every fish that can be identified with 100% certainty from a single frame is marked.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

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Modalities archive 2025-07-28

Languages archive 2025-07-28

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Variants archive 2025-07-28

  • FISHTRAC

1 variant name, as the archive lists them.

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