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Apr 11, 2019 · A promising approach is based on deep networks trained on human-annotated images. We provide a challenge dataset to explore whether such ...
Download the Caltech Camera Traps dataset, which was used for the iWildCam 2018 Competition, at LILA.science. Data Challenges. Camera trap data provides ...
A challenge dataset is provided to explore whether automatic solutions for annotating camera trap data generalize to novel locations, since systems that are ...
Apr 24, 2019 · Camera traps are a valuable tool for studying biodiversity, but research using this data is limited by the speed of human annotation.
This dataset is the first to focus on the need for generalization in automated solutions for camera trap data.
We have prepared a challenge where the training data and test data are from different cameras spread across the globe. The set of species seen in each camera ...
WILDS is a curated collection of benchmark datasets that represent distribution shifts faced in the wild.
Checkout the iWildCam Competition Github repo for the specifics of the dataset and download links. The competition itself is being hosted on Kaggle.
Sara Beery, Grant Van Horn, Oisin Mac Aodha, Pietro Perona: The iWildCam 2018 Challenge Dataset. CoRR abs/1904.05986 (2019). manage site settings.