16 citations · 29 across the 6 of their papers we have counts for
6 papers
The iNaturalist Sounds Dataset
Mustafa Chasmai, Alexander Shepard, Subhransu Maji +1
We present the iNaturalist Sounds Dataset (iNatSounds), a collection of 230,000 audio files capturing sounds from over 5,500 species, contributed by more than 27,000 recordists wor…
Feedforward Few-shot Species Range Estimation
Christian Lange, Max Hamilton, Elijah Cole +6
Knowing where a particular species can or cannot be found on Earth is crucial for ecological research and conservation efforts. By mapping the spatial ranges of all species, we wou…
INQUIRE: A Natural World Text-to-Image Retrieval Benchmark
Edward Vendrow, Omiros Pantazis, Alexander Shepard +5
We introduce INQUIRE, a text-to-image retrieval benchmark designed to challenge multimodal vision-language models on expert-level queries. INQUIRE includes iNaturalist 2024 (iNat24…
Combining Observational Data and Language for Species Range Estimation
Max Hamilton, Christian Lange, Elijah Cole +5
Species range maps (SRMs) are essential tools for research and policy-making in ecology, conservation, and environmental management. However, traditional SRMs rely on the availabil…
Spatial Implicit Neural Representations for Global-Scale Species Mapping
Elijah Cole, Grant Van Horn, Christian Lange +5
Estimating the geographical range of a species from sparse observations is a challenging and important geospatial prediction problem. Given a set of locations where a species has b…
The iNaturalist Species Classification and Detection Dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song +6
Existing image classification datasets used in computer vision tend to have a uniform distribution of images across object categories. In contrast, the natural world is heavily imb…