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.

翻译：我们提出了FindingEmo，一个包含25,000张图像标注的新数据集，专门针对情绪识别任务设计。与现有数据集不同，该数据集聚焦于描绘多人在各种自然社交场景中的复杂场景，并以整体方式对图像进行标注，从而超越了传统上仅关注人脸或单一个体的局限。标注维度包括效价、唤醒度和情绪标签，标注工作通过Prolific平台完成。除标注数据外，我们还发布了指向原始图像的URL列表以及所有相关源代码。