mlsanityData to 7 Oct 2026

Florida Wildlife Camera Trap Dataset

arXiv 2106.12628 ↗First posted 23 Jun 2021cs.CV eess.IVcited by 7

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Abstract (arXiv)

Trail camera imagery has increasingly gained popularity amongst biologists for conservation and ecological research. Minimal human interference required to operate camera traps allows capturing unbiased species activities. Several studies - based on human and wildlife interactions, migratory patterns of various species, risk of extinction in endangered populations - are limited by the lack of rich data and the time-consuming nature of manually annotating trail camera imagery. We introduce a challenging wildlife camera trap classification dataset collected from two different locations in Southwestern Florida, consisting of 104,495 images featuring visually similar species, varying illumination conditions, skewed class distribution, and including samples of endangered species, i.e. Florida panthers. Experimental evaluations with ResNet-50 architecture indicate that this image classification-based dataset can further push the advancements in wildlife statistical modeling. We will make the dataset publicly available.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 2 of its 17 references that are in the map. First posted on arXiv 23 Jun 2021.

Builds on

2 of 17 references.

References · 2

  1. 2018Past, Present, and Future Approaches Using Computer Vision for Animal Re-Identification from Camera Trap Datacited by 45
  2. 2016Towards Automatic Wild Animal Monitoring: Identification of Animal Species in Camera-trap Images using Very Deep Convolutional Neural Networkscited by 28

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Cited by year

Citing papers per year: 2022: 2; 2023: 3; 2024: 1; 2025: 1.

7 papers.