{"url":"/dataset/celebamask-hq","name":"CelebAMask-HQ","full_name":null,"description_markdown":"**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.\r\n\r\nSource: [https://github.com/switchablenorms/CelebAMask-HQ](https://github.com/switchablenorms/CelebAMask-HQ)\r\nImage Source: [https://github.com/switchablenorms/CelebAMask-HQ](https://github.com/switchablenorms/CelebAMask-HQ)","description_withheld":null,"homepage":"https://github.com/switchablenorms/CelebAMask-HQ","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/maskgan-towards-diverse-and-interactive","title":"MaskGAN: Towards Diverse and Interactive Facial Image Manipulation","first_author":"Cheng-Han Lee","url":null},"license":{"name":"Custom (non-commercial)","url":"https://github.com/switchablenorms/CelebAMask-HQ#dataset-agreement"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Generation","url":"/task/image-generation","datasets_with_task":"/datasets/task/image-generation"},{"name":"Image-to-Image Translation","url":"/task/image-to-image-translation","datasets_with_task":"/datasets/task/image-to-image-translation"},{"name":"Reconstruction","url":"/task/reconstruction","datasets_with_task":"/datasets/task/reconstruction"},{"name":"Conditional Image Generation","url":"/task/conditional-image-generation","datasets_with_task":"/datasets/task/conditional-image-generation"},{"name":"Pose Transfer","url":"/task/pose-transfer","datasets_with_task":"/datasets/task/pose-transfer"},{"name":"Face Parsing","url":"/task/face-parsing","datasets_with_task":"/datasets/task/face-parsing"},{"name":"3D-Aware Image Synthesis","url":"/task/3d-aware-image-synthesis","datasets_with_task":"/datasets/task/3d-aware-image-synthesis"},{"name":"Image Manipulation","url":"/task/image-manipulation","datasets_with_task":"/datasets/task/image-manipulation"}],"languages":[],"variants":["CelebAMask-HQ"],"data_loaders":[{"repo":"https://github.com/switchablenorms/CelebAMask-HQ","url":"https://github.com/switchablenorms/CelebAMask-HQ","frameworks":["pytorch"]}],"num_papers_in_archive":164,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/face-parsing-on-celebamask-hq","task":"Face Parsing","dataset_variant":"CelebAMask-HQ","rows":7,"metrics":["Mean F1"],"first_row_in_archive_order":{"model":"FaRL-B","paper":"/paper/general-facial-representation-learning-in-a","metrics":{"Mean F1":"89.56"},"code_links":[{"title":"FacePerceiver/FaRL","url":"https://github.com/FacePerceiver/FaRL"},{"title":"willyfh/farl-face-segmentation","url":"https://github.com/willyfh/farl-face-segmentation"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/3d-aware-image-synthesis-on-celebamask-hq","task":"3D-Aware Image Synthesis","dataset_variant":"CelebAMask-HQ","rows":3,"metrics":["FID","IS"],"first_row_in_archive_order":{"model":"Sem2NeRF","paper":"/paper/sem2nerf-converting-single-view-semantic","metrics":{"FID":"41.52","IS":"2.03"},"code_links":[{"title":"donydchen/sem2nerf","url":"https://github.com/donydchen/sem2nerf"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/conditional-image-generation-on-celebamask-hq","task":"Conditional Image Generation","dataset_variant":"CelebAMask-HQ","rows":1,"metrics":["FID","LPIPS","mIoU"],"first_row_in_archive_order":{"model":"SCDM","paper":"/paper/stochastic-conditional-diffusion-models-for","metrics":{"FID":"17.4","LPIPS":"0.418","mIoU":"77.2"},"code_links":[{"title":"mlvlab/scdm","url":"https://github.com/mlvlab/scdm"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/pose-transfer-on-celebamask-hq","task":"Pose Transfer","dataset_variant":"CelebAMask-HQ","rows":1,"metrics":["S-FID"],"first_row_in_archive_order":{"model":"SCAM","paper":"/paper/scam-transferring-humans-between-images-with","metrics":{"S-FID":"19.8"},"code_links":[{"title":"nicolas-dufour/SCAM","url":"https://github.com/nicolas-dufour/SCAM"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/reconstruction-on-celebamask-hq","task":"Reconstruction","dataset_variant":"CelebAMask-HQ","rows":1,"metrics":["PSNR","R-FID"],"first_row_in_archive_order":{"model":"SCAM","paper":"/paper/scam-transferring-humans-between-images-with","metrics":{"PSNR":"21.9","R-FID":"15.5"},"code_links":[{"title":"nicolas-dufour/SCAM","url":"https://github.com/nicolas-dufour/SCAM"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/segface-face-segmentation-of-long-tail","title":"SegFace: Face Segmentation of Long-Tail Classes","date":"2024-12-11","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/stochastic-conditional-diffusion-models-for","title":"Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis","date":"2024-02-26","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":1,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/scam-transferring-humans-between-images-with","title":"SCAM! Transferring humans between images with Semantic Cross Attention Modulation","date":"2022-10-10","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/decoupled-multi-task-learning-with-cyclical","title":"Decoupled Multi-task Learning with Cyclical Self-Regulation for Face Parsing","date":"2022-03-28","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/sem2nerf-converting-single-view-semantic","title":"Sem2NeRF: Converting Single-View Semantic Masks to Neural Radiance Fields","date":"2022-03-21","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":2,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/general-facial-representation-learning-in-a","title":"General Facial Representation Learning in a Visual-Linguistic Manner","date":"2021-12-06","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":1,"samples_unverified":4,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/adaptive-graph-representation-learning-and","title":"AGRNet: Adaptive Graph Representation Learning and Reasoning for Face Parsing","date":"2021-01-18","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/edge-aware-graph-representation-learning-and","title":"Edge-aware Graph Representation Learning and Reasoning for Face Parsing","date":"2020-07-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/ehanet-an-effective-hierarchical-aggregation","title":"EHANet: An Effective Hierarchical Aggregation Network for Face Parsing","date":"2020-04-07","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/accurate-facial-image-parsing-at-real-time","title":"Accurate facial image parsing at real-time speed","date":"2019-04-09","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":13,"samples_ran":4,"samples_unverified":9,"pointer_only_for_licence":4,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}