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Thus, methods that achieve accurate performance on the 300-W database can demonstrate the same accuracy in most realistic cases.\r\nMany images of the database contain more than one annotated faces (293 images with 1 face, 53 images with 2 faces and 53 images with [3, 7] faces). Consequently, the database consists of 600 annotated face instances, but 399 unique images. Finally, there is a large variety of face sizes. Specifically, 49.3% of the faces have size in the range [48.6k, 2.0M] and the overall mean size is 85k (about 292 × 292) pixels.\r\n\r\nSource: [https://ibug.doc.ic.ac.uk/media/uploads/documents/sagonas_2016_imavis.pdf](https://ibug.doc.ic.ac.uk/media/uploads/documents/sagonas_2016_imavis.pdf)\r\nImage Source: [https://www.researchgate.net/profile/Xuanyi_Dong/publication/323722412/figure/fig1/AS:679426136227845@1538999222829/Face-samples-from-300-W-dataset-Different-faces-have-different-styles-whereas-the-style_Q640.jpg](https://www.researchgate.net/profile/Xuanyi_Dong/publication/323722412/figure/fig1/AS:679426136227845@1538999222829/Face-samples-from-300-W-dataset-Different-faces-have-different-styles-whereas-the-style_Q640.jpg)","description_withheld":null,"homepage":"https://ibug.doc.ic.ac.uk/resources/300-W/","introduced_date":"2013-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"300 Faces in-the-Wild Challenge: The First Facial Landmark Localization Challenge","first_author":null,"url":"https://doi.org/10.1109/ICCVW.2013.59"},"license":{"name":"Custom (research-only, non-commercial)","url":"https://ibug.doc.ic.ac.uk/resources/300-W/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Pose Estimation","url":"/task/pose-estimation","datasets_with_task":"/datasets/task/pose-estimation"},{"name":"3D Reconstruction","url":"/task/3d-reconstruction","datasets_with_task":"/datasets/task/3d-reconstruction"},{"name":"Face Alignment","url":"/task/face-alignment","datasets_with_task":"/datasets/task/face-alignment"},{"name":"Facial Landmark Detection","url":"/task/facial-landmark-detection","datasets_with_task":"/datasets/task/facial-landmark-detection"},{"name":"2D Pose Estimation","url":"/task/2d-pose-estimation","datasets_with_task":"/datasets/task/2d-pose-estimation"},{"name":"Unsupervised Facial Landmark Detection","url":"/task/unsupervised-facial-landmark-detection","datasets_with_task":"/datasets/task/unsupervised-facial-landmark-detection"}],"languages":[],"variants":["300W","300W (Full)","300W Split 2","300W Split 2 (300W-LP)"],"data_loaders":[{"repo":"https://github.com/activeloopai/Hub","url":"https://docs.activeloop.ai/datasets/300w-dataset","frameworks":["tf","pytorch"]},{"repo":"https://github.com/open-mmlab/mmpose","url":"https://github.com/open-mmlab/mmpose/blob/master/docs/tasks/2d_face_keypoint.md#300w-dataset","frameworks":["pytorch"]}],"num_papers_in_archive":206,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/face-alignment-on-300w","task":"Face Alignment","dataset_variant":"300W","rows":48,"metrics":["NME_inter-ocular (%, Full)","NME_inter-ocular (%, Common)","NME_inter-ocular (%, Challenge)","NME_inter-pupil (%, Full)","NME_inter-pupil (%, Common)","NME_inter-pupil (%, Challenge)"],"first_row_in_archive_order":{"model":"STAR","paper":"/paper/star-loss-reducing-semantic-ambiguity-in-1","metrics":{"NME_inter-ocular (%, Challenge)":"4.32","NME_inter-ocular (%, Common)":"2.52","NME_inter-ocular (%, Full)":"2.87","NME_inter-pupil (%, Challenge)":"6.22","NME_inter-pupil (%, Common)":"3.5","NME_inter-pupil (%, Full)":"4.03"},"code_links":[{"title":"zhenglinzhou/star","url":"https://github.com/zhenglinzhou/star"}]},"note":"rows are the archive's own order at snapshot; 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