The HELEN dataset is composed of 2330 face images of 400×400 pixels with labeled facial components generated through manually-annotated contours along eyes, eyebrows, nose, lips and jawline.
197 PAPERS • 1 BENCHMARK
CelebAMask-HQ is a large-scale face image dataset that has 30,000 high-resolution face images selected from the CelebA dataset by following CelebA-HQ. Each image has segmentation mask of facial attributes corresponding to CelebA.
147 PAPERS • 4 BENCHMARKS
A large-scale Landmark guided face Parsing dataset (LaPa) for face parsing. It consists of more than 22,000 facial images with abundant variations in expression, pose and occlusion, and each image of LaPa is provided with a 11-category pixel-level label map and 106-point landmarks.
10 PAPERS • 1 BENCHMARK
We introduce a large-scale image dataset EasyPortrait for portrait segmentation and face parsing. Proposed dataset can be used in several tasks, such as background removal in conference applications, teeth whitening, face skin enhancement, red eye removal or eye colorization, and so on.
2 PAPERS • NO BENCHMARKS YET
iBugMask is an in-the-wild face parsing dataset that contains 1,000 challenging face images and manually annotated labels for 11 semantic classes: background, facial skin, left/right brow, left/right eye, nose, upper/lower lip, inner mouth, and hair. The images are curated from challenging in-the-wild face alignment datasets, including 300W and Menpo. Compared with the existing face parsing datasets, iBugMask contains in-the-wild scenarios such as “party” and “conference”, which include more challenging appearance variations or multiple faces. There is a larger number of profile faces. More expressions other than ”neutral” and ”smile” are also included (e.g. ”surprise” and ”scream”). The dataset can be downloaded on here.
2 PAPERS • 1 BENCHMARK