Multiple object tracking (MOT) technology has made significant progress in terrestrial applications, but underwater tracking scenarios remain underexplored despite their importance to marine ecology and aquaculture. We present Multiple Fish Tracking Dataset 2025 (MFT25), the first comprehensive dataset specifically designed for underwater multiple fish tracking, featuring 15 diverse video sequences with 408,578 meticulously annotated bounding boxes across 48,066 frames.
Download the MFT25 dataset from BaiduYun:
Dataset includes:
Download our pretrained models:
Models include:
Method | Class | Year | HOTA↑ | IDF1↑ |
---|---|---|---|---|
FairMOT | JDE | 2021 | 22.226 | 26.867 |
CMFTNet | JDE | 2022 | 22.432 | 27.659 |
TransTrack | TF | 2021 | 30.426 | 35.215 |
TransCenter | TF | 2023 | 27.896 | 30.278 |
TrackFormer | TF | 2022 | 30.361 | 35.285 |
TFMFT | TF | 2024 | 25.440 | 33.950 |
SORT | SDE | 2016 | 29.063 | 34.119 |
ByteTrack | SDE | 2022 | 31.758 | 40.355 |
BoT-SORT | SDE | 2022 | 26.848 | 36.847 |
OC-SORT | SDE | 2023 | 25.017 | 34.620 |
Deep-OC-SORT | SDE | 2023 | 24.848 | 34.176 |
HybridSORT | SDE | 2024 | 32.258 | 38.421 |
HybridSORT† | SDE | 2024 | 32.705 | 41.727 |
SU-T (Ours) | SDE | 2025 | 33.351 | 41.717 |
SU-T† (Ours) | SDE | 2025 | 34.067 | 44.643 |