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.