MammAlps - A multi-view video behavior monitoring dataset of wild mammals in the Swiss Alps

MammAlps is a multimodal and multi-view dataset of wildlife behavior monitoring. Nine camera-traps were placed at three monitoring sites in the Swiss National Park, from which we curated over 14 hours of video with audio, 2D segmentation maps and 8.5 hours of individual tracks densely labeled for species and behavior.  

Along with the data, we propose two benchmarks:

• Benchmark I - Multimodal species and behavior recognition: Based on 6`135 single clips centered on the animal, we propose a hierarchical and multimodal animal behavior recognition benchmark using audio, video and reference scene segmentation maps as inputs.
• Benchmark II - Multi-view Long-term event understanding: a second ecology-oriented benchmark aiming at identifying activities, species, number of individuals and meteorological conditions from 397 multi-view and long-term ecological events, including false positive triggers.

General information

Authors: Valentin Gabeff, Haozhe Qi, Brendan Flaherty, Gencer Sümbül, Alexander Mathis, Devis Tuia
Affiliation: All authors were affiliated to the Ecole Polytechnique Fédérale de Lausanne (EPFL) at the time of the study
Date of collection: 08.2023 - 10.2023 (MM.YYYY - MM.YYYY)
Geolocation data: Swiss National Park, Zernez, Switzerland
Associated publication URL: https://arxiv.org/abs/2503.18223
Funding: This project was partially funded by EPFL's SV-ENAC I-PhD program (G.V.), Boehringer Ingelheim Fonds PhD stipend (H.Q.) and Swiss SNF grant (320030-227871)

Dataset availability

License: This dataset is released under the non-commercial CC BY-NC 4.0 license.

Citation : When using the dataset, please use the following citation. The article is in press for CVPR, we will update the citation. 

@article{gabeff2025mammalps,
      title={MammAlps: A multi-view video behavior monitoring dataset of wild mammals in the Swiss Alps},
      author={Valentin Gabeff and Haozhe Qi and Brendan Flaherty and Gencer Sumbül and Alexander Mathis and Devis Tuia},
      year={2025},
      journal={arXiv},
      doi={10.48550/arXiv.2503.18223},
}

Repository URL: https://zenodo.org/uploads/15040900

Repository DOI: 10.5281/zenodo.15040900

Dataset version: v3

Acknowledgements

We thank members of the Mathis Group for Computational Neuroscience & AI (EPFL) and of the Environmental Computational Science and Earth Observation Laboratory (EPFL) for their feedback and fieldwork efforts. We also thank members of the Swiss National Park monitoring team for their support and feedback. The project was approved by the Research Commission of the National Park.

Change log

• [03.06.2025]: Fix few misaligned dense annotation files.
• [26.05.2025]: Dense annotations release.
• [02.04.2025]: Data release for Benchmark I and Benchmark II.