The EasyPortrait dataset was developed to enhance video conferencing apps with features like background removal and skin enhancement. It contains 40,000 indoor photos with fine-grained segmentation masks, catering to diverse subjects, head poses, and specific accessories. The dataset's annotation process involved unique rules for classes like skin, teeth, and occlusions.
The authors conducted ablation studies to highlight the significance of data quantity and head pose diversity in training robust models. Cross-dataset evaluations demonstrated EasyPortrait's superior generalization ability compared to other datasets in both portrait segmentation and face parsing tasks.
Overall, the EasyPortrait dataset offers a comprehensive solution for improving user experience in video conferencing through advanced computer vision techniques.
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by Karina Kvanc... at arxiv.org 03-08-2024
https://arxiv.org/pdf/2304.13509.pdfDeeper Inquiries