  We introduce a new wildlife re-identification dataset WildlifeReID-10k with
more than 214k images of 10k individual animals. It is a collection of 30
existing wildlife re-identification datasets with additional processing steps.
WildlifeReID-10k contains animals as diverse as marine turtles, primates,
birds, African herbivores, marine mammals and domestic animals. Due to the
ubiquity of similar images in datasets, we argue that the standard (random)
splits into training and testing sets are inadequate for wildlife
re-identification and propose a new similarity-aware split based on the
similarity of extracted features. To promote fair method comparison, we include
similarity-aware splits both for closed-set and open-set settings, use
MegaDescriptor - a foundational model for wildlife re-identification - for
baseline performance and host a leaderboard with the best results. We publicly
publish the dataset and the codes used to create it in the wildlife-datasets
library, making WildlifeReID-10k both highly curated and easy to use.
