DogFLW: Dog Facial Landmarks in the Wild Dataset
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Abstract (arXiv)
Affective computing for animals is a rapidly expanding research area that is going deeper than automated movement tracking to address animal internal states, like pain and emotions. Facial expressions can serve to communicate information about these states in mammals. However, unlike human-related studies, there is a significant shortage of datasets that would enable the automated analysis of animal facial expressions. Inspired by the recently introduced Cat Facial Landmarks in the Wild dataset, presenting cat faces annotated with 48 facial anatomy-based landmarks, in this paper, we develop an analogous dataset containing 3,274 annotated images of dogs. Our dataset is based on a scheme of 46 facial anatomy-based landmarks. The DogFLW dataset is available from the corresponding author upon a reasonable request.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 16 of its 50 references that are in the map. First posted on arXiv 19 May 2024.
Builds on
16 of 50 references.
References · 16
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4 more
- 2015Human and Sheep Facial Landmarks Localisation by Triplet Interpolated Featurescited by 9
- 2023CatFLW: Cat Facial Landmarks in the Wild Datasetcited by 5
- 2023Automated Detection of Cat Facial Landmarkscited by 3
- 2018A Two-Step Learning Method For Detecting Landmarks on Faces From Different Domainscited by 1
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Citing papers per year: 2025: 1.
1 paper.