Summary of Findingemo: An Image Dataset For Emotion Recognition in the Wild, by Laurent Mertens and Elahe’ Yargholi and Hans Op De Beeck and Jan Van Den Stock and Joost Vennekens
FindingEmo: An Image Dataset for Emotion Recognition in the Wild
by Laurent Mertens, Elahe’ Yargholi, Hans Op de Beeck, Jan Van den Stock, Joost Vennekens
First submitted to arxiv on: 2 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces FindingEmo, a novel image dataset designed for emotion recognition. It contains 25k images with complex scenes featuring multiple people in naturalistic settings, annotated with valence, arousal, and emotion labels. The annotations were gathered using Prolific, moving beyond traditional focus on faces or single individuals. The release includes the list of URLs pointing to original images, as well as associated source code. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary FindingEmo is a new image dataset that helps computers recognize emotions in photos. It contains 25,000 pictures with many people in real-life situations. This is different from other datasets that only focus on individual faces or simple scenes. The pictures are labeled to show how positive or negative they make you feel, and how much excitement or calmness they convey. The dataset also includes the original image URLs and the code used to create it. |
