# AnimalClue YOLO Datasets


## AnimalClue: Recognizing Animals by their Traces  
### 📌 ICCV 2025 Highlight

This repository is part of the **AnimalClue** project, which explores the recognition of wild animals **from indirect clues** such as feathers, footprints, feces, eggs, and bones. These datasets are designed for object detection training using **YOLO format**.

Each image filename is linked to an observation ID, and any use of the image must comply with the license associated with the corresponding observation.

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## 📂 Included Datasets

This repository is one of five closely related datasets:

- [`feather_yolo`](https://huggingface.co/risashinoda/feather_yolo)
- [`egg_yolo`](https://huggingface.co/risashinoda/egg_yolo)
- [`feces_yolo`](https://huggingface.co/risashinoda/feces_yolo)
- [`footprint_yolo`](https://huggingface.co/risashinoda/footprint_yolo)
- [`bone_yolo`](https://huggingface.co/risashinoda/bone_yolo)

## Citation
```
@inproceedings{shinoda2025animalclue,
  title={AnimalClue: Recognizing Animals by Their Traces},
  author={Shinoda, Risa and Inoue, Nakamasa and Laina, Iro and Rupprecht, Christian and Kataoka, Hirokatsu},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={14776--14786},
  year={2025}
}
```

Please consider citing the related paper as well.
```
@INPROCEEDINGS{10648043,
  author={Shinoda, Risa and Shiohara, Kaede},
  booktitle={2024 IEEE International Conference on Image Processing (ICIP)}, 
  title={OpenAnimalTracks: A Dataset for Animal Track Recognition}, 
  year={2024},
  volume={},
  number={},
  pages={110-116},
  doi={10.1109/ICIP51287.2024.10648043}}
```