FindingEmo: An Image Dataset for Emotion Recognition in the Wild

Abstract

We introduce FindingEmo, a new image dataset containing annotations for 25k images, specifically tailored to Emotion Recognition. Contrary to existing datasets, it focuses on complex scenes depicting multiple people in various naturalistic, social settings, with images being annotated as a whole, thereby going beyond the traditional focus on faces or single individuals. Annotated dimensions include Valence, Arousal and Emotion label, with annotations gathered using Prolific. Together with the annotations, we release the list of URLs pointing to the original images, as well as all associated source code.

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Cite

Text

Mertens et al. "FindingEmo: An Image Dataset for Emotion Recognition in the Wild." Neural Information Processing Systems, 2024. doi:10.52202/079017-0161

Markdown

[Mertens et al. "FindingEmo: An Image Dataset for Emotion Recognition in the Wild." Neural Information Processing Systems, 2024.](https://mlanthology.org/neurips/2024/mertens2024neurips-findingemo/) doi:10.52202/079017-0161

BibTeX

@inproceedings{mertens2024neurips-findingemo,
  title     = {{FindingEmo: An Image Dataset for Emotion Recognition in the Wild}},
  author    = {Mertens, Laurent and Yargholi, Elahe' and de Beeck, Hans Op and Van den Stock, Jan and Vennekens, Joost},
  booktitle = {Neural Information Processing Systems},
  year      = {2024},
  doi       = {10.52202/079017-0161},
  url       = {https://mlanthology.org/neurips/2024/mertens2024neurips-findingemo/}
}