{"url":"/dataset/cofw","name":"COFW","full_name":"Caltech Occluded Faces in the Wild","description_markdown":"The **Caltech Occluded Faces in the Wild** (**COFW**) dataset is designed to present faces in real-world conditions. Faces show large variations in shape and occlusions due to differences in pose, expression, use of accessories such as sunglasses and hats and interactions with objects (e.g. food, hands, microphones,
etc.). All images were hand annotated using the same 29 landmarks as in LFPW. Both the landmark positions as well as their occluded/unoccluded state were annotated. The faces are occluded to different degrees, with large variations in the type of occlusions encountered. COFW has an average occlusion of over 23.\r\n\r\nSource: [http://www.vision.caltech.edu/xpburgos/ICCV13/#dataset](http://www.vision.caltech.edu/xpburgos/ICCV13/#dataset)\r\nImage Source: [http://www.vision.caltech.edu/xpburgos/ICCV13/#dataset](http://www.vision.caltech.edu/xpburgos/ICCV13/#dataset)","description_withheld":null,"homepage":"http://www.vision.caltech.edu/xpburgos/ICCV13/#dataset","introduced_date":"2013-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"Robust Face Landmark Estimation under Occlusion","first_author":null,"url":"https://doi.org/10.1109/ICCV.2013.191"},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"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":"Head Pose Estimation","url":"/task/head-pose-estimation","datasets_with_task":"/datasets/task/head-pose-estimation"}],"languages":[],"variants":["COFW","COFW-68","COFW-68 (300WLP)"],"data_loaders":[{"repo":"https://github.com/open-mmlab/mmpose","url":"https://github.com/open-mmlab/mmpose/blob/master/docs/tasks/2d_face_keypoint.md#cofw-dataset","frameworks":["pytorch"]}],"num_papers_in_archive":114,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/face-alignment-on-cofw","task":"Face Alignment","dataset_variant":"COFW","rows":28,"metrics":["NME (inter-ocular)","Recall at 80% precision (Landmarks Visibility)","NME (inter-pupil)"],"first_row_in_archive_order":{"model":"FiFA","paper":"/paper/fiducial-focus-augmentation-for-facial","metrics":{"NME (inter-ocular)":"2.96"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/face-alignment-on-cofw-68","task":"Face Alignment","dataset_variant":"COFW-68","rows":7,"metrics":["NME (inter-ocular)","NME (box)","AUC@7 (box)"],"first_row_in_archive_order":{"model":"SPIGA","paper":"/paper/shape-preserving-facial-landmarks-with-graph","metrics":{"AUC@7 (box)":"64.1","NME (box)":"2.52","NME (inter-ocular)":"3.93"},"code_links":[{"title":"andresprados/spiga","url":"https://github.com/andresprados/spiga"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/face-alignment-on-cofw-68-300wlp","task":"Face Alignment","dataset_variant":"COFW-68 (300WLP)","rows":4,"metrics":["NME (box)","AUC@7"],"first_row_in_archive_order":{"model":"SH-FAN","paper":"/paper/subpixel-heatmap-regression-for-facial","metrics":{"AUC@7":"64.9","NME (box)":"2.47"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/facial-landmark-detection-on-cofw","task":"Facial Landmark Detection","dataset_variant":"COFW","rows":2,"metrics":["NME (inter-pupil)","NME (inter-ocular)","NME"],"first_row_in_archive_order":{"model":"D-ViT","paper":"/paper/cascaded-dual-vision-transformer-for-accurate","metrics":{"NME (inter-pupil)":"4.13"},"code_links":[{"title":"Human3DAIGC/AccurateFacialLandmarkDetection","url":"https://github.com/Human3DAIGC/AccurateFacialLandmarkDetection"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/head-pose-estimation-on-cofw","task":"Head Pose Estimation","dataset_variant":"COFW","rows":1,"metrics":["MAE pitch (º)","MAE yaw (º)"],"first_row_in_archive_order":{"model":"ASMNet","paper":"/paper/deep-active-shape-model-for-face-alignment","metrics":{"MAE pitch (º)":"2.72","MAE yaw (º)":"2.91"},"code_links":[{"title":"aliprf/ASMNet","url":"https://github.com/aliprf/ASMNet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/cascaded-dual-vision-transformer-for-accurate","title":"Cascaded Dual Vision Transformer for Accurate Facial Landmark Detection","date":"2024-11-08","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/fiducial-focus-augmentation-for-facial","title":"Fiducial Focus Augmentation for Facial Landmark Detection","date":"2024-02-23","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/star-loss-reducing-semantic-ambiguity-in-1","title":"STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection","date":"2023-06-05","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":4,"samples_unverified":0,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/shape-preserving-facial-landmarks-with-graph","title":"Shape Preserving Facial Landmarks with Graph Attention Networks","date":"2022-10-13","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/towards-accurate-facial-landmark-detection-1","title":"Towards Accurate Facial Landmark Detection via Cascaded Transformers","date":"2022-08-23","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/acr-loss-adaptive-coordinate-based-regression","title":"ACR Loss: Adaptive Coordinate-based Regression Loss for Face Alignment","date":"2022-03-29","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/sparse-local-patch-transformer-for-robust","title":"Sparse Local Patch Transformer for Robust Face Alignment and Landmarks Inherent Relation Learning","date":"2022-03-13","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/occlusion-robust-face-alignment-using-a","title":"Occlusion-Robust Face Alignment Using a Viewpoint-Invariant Hierarchical Network Architecture","date":"2022-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/facial-landmark-points-detection-using","title":"Facial Landmark Points Detection Using Knowledge Distillation-Based Neural Networks","date":"2021-11-13","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/subpixel-heatmap-regression-for-facial","title":"Subpixel Heatmap Regression for Facial Landmark Localization","date":"2021-11-03","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/revisiting-quantization-error-in-face","title":"Revisiting Quantization Error in Face Alignment","date":"2021-09-13","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/when-liebig-s-barrel-meets-facial-landmark","title":"When Liebig's Barrel Meets Facial Landmark Detection: A Practical Model","date":"2021-05-27","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/hih-towards-more-accurate-face-alignment-via","title":"HIH: Towards More Accurate Face Alignment via Heatmap in Heatmap","date":"2021-04-07","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/pre-training-strategies-and-datasets-for","title":"Pre-training strategies and datasets for facial representation learning","date":"2021-03-30","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/deep-active-shape-model-for-face-alignment","title":"ASMNet: a Lightweight Deep Neural Network for Face Alignment and Pose Estimation","date":"2021-02-27","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/improving-robustness-of-facial-landmark","title":"Improving Robustness of Facial Landmark Detection by Defending Against Adversarial Attacks","date":"2021-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/multi-task-head-pose-estimation-in-the-wild-1","title":"Multi-task head pose estimation in-the-wild","date":"2020-12-22","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/atf-towards-robust-face-alignment-via","title":"ATF: Towards Robust Face Alignment via Leveraging Similarity and Diversity across Different Datasets","date":"2020-10-12","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/propagationnet-propagate-points-to-curve-to-1","title":"PropagationNet: Propagate Points to Curve to Learn Structure Information","date":"2020-06-25","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/fast-and-accurate-structure-coherence","title":"Fast and Accurate: Structure Coherence Component for Face Alignment","date":"2020-06-21","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/structured-landmark-detection-via-topology","title":"Structured Landmark Detection via Topology-Adapting Deep Graph Learning","date":"2020-04-17","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/luvli-face-alignment-estimating-landmarks","title":"LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood","date":"2020-04-06","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/pixel-in-pixel-net-towards-efficient-facial","title":"Pixel-in-Pixel Net: Towards Efficient Facial Landmark Detection in the Wild","date":"2020-03-08","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":17,"samples_ran":2,"samples_unverified":15,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/cascade-of-encoder-decoder-cnns-with-learned","title":"Cascade of Encoder-Decoder CNNs with Learned Coordinates Regressor for Robust Facial Landmarks Detection","date":"2019-10-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/face-alignment-with-kernel-density-deep","title":"Face Alignment With Kernel Density Deep Neural Network","date":"2019-10-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/190807919","title":"Deep High-Resolution Representation Learning for Visual Recognition","date":"2019-08-20","rows_on_this_dataset":2,"code_links":42,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":34,"samples_ran":3,"samples_unverified":31,"pointer_only_for_licence":16,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/high-resolution-representations-for-labeling","title":"High-Resolution Representations for Labeling Pixels and Regions","date":"2019-04-09","rows_on_this_dataset":1,"code_links":39,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":18,"samples_ran":3,"samples_unverified":15,"pointer_only_for_licence":5,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/face-alignment-using-a-3d-deeply-initialized","title":"Face Alignment using a 3D Deeply-initialized Ensemble of Regression Trees","date":"2019-02-05","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/stacked-dense-u-nets-with-dual-transformers","title":"Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment","date":"2018-12-05","rows_on_this_dataset":1,"code_links":3,"syntology":null},{"paper":"/paper/a-deeply-initialized-coarse-to-fine-ensemble","title":"A Deeply-initialized Coarse-to-fine Ensemble of Regression Trees for Face Alignment","date":"2018-09-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/look-at-boundary-a-boundary-aware-face","title":"Look at Boundary: A Boundary-Aware Face Alignment Algorithm","date":"2018-05-26","rows_on_this_dataset":2,"code_links":2,"syntology":null},{"paper":"/paper/disentangling-3d-pose-in-a-dendritic-cnn-for","title":"Disentangling 3D Pose in A Dendritic CNN for Unconstrained 2D Face Alignment","date":"2018-02-19","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/wing-loss-for-robust-facial-landmark","title":"Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks","date":"2017-11-17","rows_on_this_dataset":1,"code_links":6,"syntology":null},{"paper":"/paper/how-far-are-we-from-solving-the-2d-3d-face","title":"How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)","date":"2017-03-21","rows_on_this_dataset":1,"code_links":8,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":15,"samples_ran":4,"samples_unverified":11,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":5,"samples_harvested":88,"samples_ran":16,"samples_unverified":72,"pointer_only_for_licence":25,"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."}