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Jun Chen,Ming Hu,Darren J. Coker,blair Costelloe,Michael L. Berumen,Sara Beery,Anna Rohrbach andMohamed Elhoseiny.

MammalNet is built around a biological mammal taxonomy spanning 17 orders, 69 families and 173 mammal categories,and includes 12 common high-level mammal behaviors (e.g. hunt, groom). We establish three benchmarks on MammalNet:standard animal and behavior recognition, compositional low-shot animal and behavior recognition, and behavior detection.

To download the required files, follow these steps:

1. Trimmed Video Files:

   wget https://mammalnet.s3.amazonaws.com/trimmed_videos.tar.gz

2. Annotation Files:

   wget https://mammalnet.s3.amazonaws.com/annotation.tar

3. Full-length Video Files:

   wget https://mammalnet.s3.amazonaws.com/full_video.tar.gz

Please referrecognition page to prepare the dataset and run code

Please referdetection page to prepare the dataset and run code

@InProceedings{Chen_2023_CVPR,    author    = {Chen, Jun and Hu, Ming and Coker, Darren J. and Berumen, Michael L. and Costelloe, Blair and Beery, Sara and Rohrbach, Anna and Elhoseiny, Mohamed},    title     = {MammalNet: A Large-Scale Video Benchmark for Mammal Recognition and Behavior Understanding},    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},    month     = {June},    year      = {2023},    pages     = {13052-13061}}