Hi everyone! 

We are happy to announce our third annual iWildCam camera trap challenge, focused on helping to automate species categorization in challenging passive-monitoring cameras placed in the wild and used by ecologists to study animal populations and behavior. The challenge is part of the Seventh Workshop on Fine-Grained Visual Categorization (FGVC7) at CVPR 2020 in Seattle.

In our first challenge, iWildCam2018, we focused on binary empty/animal classification. In the second year of our challenge, iWildCam2019, we focused on generalization to an out-of-sample part of the world with a non-identical set of species and had 336 teams compete from around the world. This year in iWildCam2020 we are focusing on multimodal data fusion as a way to improve generalization to new camera locations across the globe by providing matched multispectral remote sensing data for each camera trap location, as well as curated subsets of iNaturalist competition data for the species in our dataset.

Looking forward to the interesting and creative solutions that you all come up with. Feel free to ask questions on kaggle, or on the competition github page!