{"url":"/dataset/realy","name":"REALY","full_name":"Region-aware benchmark based on the LYHM","description_markdown":"The REALY benchmark aims to introduce a region-aware evaluation pipeline to measure the fine-grained normalized mean square error (NMSE) of 3D face reconstruction methods from under-controlled image sets.\r\n\r\nGiven the reconstructed mesh from the 2D image in REALY by a specific method, the REALY benchmark calculates the similarity of ground-truth scans on four regions (nose, mouth, forehead, cheek) with the predicted mesh.","description_withheld":null,"homepage":"https://www.realy3dface.com/","introduced_date":"2022-03-18","introduced_date_note":null,"introduced_by":{"paper":"/paper/realy-rethinking-the-evaluation-of-3d-face","title":"REALY: Rethinking the Evaluation of 3D Face Reconstruction","first_author":"Zenghao Chai","url":null},"license":{"name":"MIT","url":"https://opensource.org/licenses/MIT"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"3D","url":"/datasets/modality/3d"},{"name":"3d meshes","url":"/datasets/modality/3d-meshes"},{"name":"RGB-D","url":"/datasets/modality/rgb-d"}],"tasks":[{"name":"3D Face Reconstruction","url":"/task/3d-face-reconstruction","datasets_with_task":"/datasets/task/3d-face-reconstruction"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["REALY","REALY (side-view)"],"data_loaders":[{"repo":"https://github.com/czh-98/REALY","url":"https://github.com/czh-98/REALY","frameworks":[]}],"num_papers_in_archive":24,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/3d-face-reconstruction-on-realy","task":"3D Face Reconstruction","dataset_variant":"REALY","rows":24,"metrics":["all","@nose","@mouth","@forehead","@cheek"],"first_row_in_archive_order":{"model":"HiFace-f","paper":"/paper/hiface-high-fidelity-3d-face-reconstruction","metrics":{"@cheek":"1.291 (±0.362)","@forehead":"1.324 (±0.334)","@mouth":"1.450 (±0.413)","@nose":"1.036 (±0.280)","all":"1.275"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/3d-face-reconstruction-on-realy-side-view","task":"3D Face Reconstruction","dataset_variant":"REALY (side-view)","rows":19,"metrics":["all","@nose","@mouth","@forehead","@cheek"],"first_row_in_archive_order":{"model":"HiFace-f","paper":"/paper/hiface-high-fidelity-3d-face-reconstruction","metrics":{"@cheek":"1.360 (±0.395)","@forehead":"1.399 (±0.388)","@mouth":"1.489 (±0.436)","@nose":"0.985 (±0.237)","all":"1.308"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/mosar-monocular-semi-supervised-model-for","title":"MoSAR: Monocular Semi-Supervised Model for Avatar Reconstruction using Differentiable Shading","date":"2023-12-20","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/3d-face-reconstruction-with-the-geometric","title":"3D Face Reconstruction with the Geometric Guidance of Facial Part Segmentation","date":"2023-12-01","rows_on_this_dataset":2,"code_links":2,"syntology":null},{"paper":"/paper/a-perceptual-shape-loss-for-monocular-3d-face","title":"A Perceptual Shape Loss for Monocular 3D Face Reconstruction","date":"2023-10-30","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/towards-realistic-generative-3d-face-models","title":"Towards Realistic Generative 3D Face Models","date":"2023-04-24","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/hiface-high-fidelity-3d-face-reconstruction","title":"HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details","date":"2023-03-20","rows_on_this_dataset":4,"code_links":0,"syntology":null},{"paper":"/paper/a-hierarchical-representation-network-for","title":"A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild Images","date":"2023-02-28","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/ffhq-uv-normalized-facial-uv-texture-dataset","title":"FFHQ-UV: Normalized Facial UV-Texture Dataset for 3D Face Reconstruction","date":"2022-11-25","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":1,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/emoca-emotion-driven-monocular-face-capture","title":"EMOCA: Emotion Driven Monocular Face Capture and Animation","date":"2022-04-24","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/towards-metrical-reconstruction-of-human","title":"Towards Metrical Reconstruction of Human Faces","date":"2022-04-13","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/synergy-between-3dmm-and-3d-landmarks-for","title":"Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry","date":"2021-10-19","rows_on_this_dataset":2,"code_links":4,"syntology":null},{"paper":"/paper/self-supervised-3d-face-reconstruction-via-1","title":"Self-Supervised 3D Face Reconstruction via Conditional Estimation","date":"2021-10-10","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/sadrnet-self-aligned-dual-face-regression","title":"SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction","date":"2021-06-06","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":0,"samples_unverified":8,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/learning-an-animatable-detailed-3d-face-model","title":"Learning an Animatable Detailed 3D Face Model from In-The-Wild Images","date":"2020-12-07","rows_on_this_dataset":4,"code_links":2,"syntology":null},{"paper":"/paper/towards-fast-accurate-and-stable-3d-dense-1","title":"Towards Fast, Accurate and Stable 3D Dense Face Alignment","date":"2020-09-21","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":6,"samples_unverified":4,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/self-supervised-monocular-3d-face","title":"Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry Consistency","date":"2020-07-24","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":16,"samples_ran":0,"samples_unverified":16,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/learning-to-regress-3d-face-shape-and","title":"Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision","date":"2019-05-16","rows_on_this_dataset":2,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":0,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/towards-high-fidelity-nonlinear-3d-face","title":"Towards High-fidelity Nonlinear 3D Face Morphable Model","date":"2019-04-09","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/accurate-3d-face-reconstruction-with-weakly","title":"Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set","date":"2019-03-20","rows_on_this_dataset":2,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":36,"samples_ran":11,"samples_unverified":25,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/ganfit-generative-adversarial-network-fitting","title":"GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction","date":"2019-02-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/joint-3d-face-reconstruction-and-dense","title":"Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network","date":"2018-03-21","rows_on_this_dataset":2,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":0,"samples_unverified":10,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/expnet-landmark-free-deep-3d-facial","title":"ExpNet: Landmark-Free, Deep, 3D Facial Expressions","date":"2018-02-02","rows_on_this_dataset":2,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":7,"samples_harvested":91,"samples_ran":18,"samples_unverified":73,"pointer_only_for_licence":3,"papers_with_no_sample_that_ran":4,"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."}