300W

300 Faces-In-The-Wild

Dataset Information
Modalities
Images
Introduced
2013
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Overview

The 300-W is a face dataset that consists of 300 Indoor and 300 Outdoor in-the-wild images. It covers a large variation of identity, expression, illumination conditions, pose, occlusion and face size. The images were downloaded from google.com by making queries such as “party”, “conference”, “protests”, “football” and “celebrities”. Compared to the rest of in-the-wild datasets, the 300-W database contains a larger percentage of partially-occluded images and covers more expressions than the common “neutral” or “smile”, such as “surprise” or “scream”.
Images were annotated with the 68-point mark-up using a semi-automatic methodology. The images of the database were carefully selected so that they represent a characteristic sample of challenging but natural face instances under totally unconstrained conditions. Thus, methods that achieve accurate performance on the 300-W database can demonstrate the same accuracy in most realistic cases.
Many 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.

Source: https://ibug.doc.ic.ac.uk/media/uploads/documents/sagonas_2016_imavis.pdf
Image 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

Variants: 300W, 300W (Full), 300W Split 2, 300W Split 2 (300W-LP)

Associated Benchmarks

This dataset is used in 3 benchmarks:

Recent Benchmark Submissions

Task Model Paper Date
Facial Landmark Detection D-ViT Cascaded Dual Vision Transformer for … 2024-11-08
Facial Landmark Detection FiFA Fiducial Focus Augmentation for Facial … 2024-02-23
2D Pose Estimation UniPose X-Pose: Detecting Any Keypoints 2023-10-12
Facial Landmark Detection SPIGA (Inter-ocular Norm) Shape Preserving Facial Landmarks with … 2022-10-13
Facial Landmark Detection CNN-CRF (Inter-ocular Norm) Deep Structured Prediction for Facial … 2020-10-18
Facial Landmark Detection AnchorFace AnchorFace: An Anchor-based Facial Landmark … 2020-07-07
Facial Landmark Detection TS3 Teacher Supervises Students How to … 2019-08-06
Facial Landmark Detection Adaloss Adaloss: Adaptive Loss Function for … 2019-08-02
3D Reconstruction ResNet What Do Single-view 3D Reconstruction … 2019-05-09
Facial Landmark Detection 3DDE (Inter-ocular Norm) Face Alignment using a 3D … 2019-02-05
Facial Landmark Detection SAN GT Style Aggregated Network for Facial … 2018-03-12
Facial Landmark Detection FPN FacePoseNet: Making a Case for … 2017-08-24
Facial Landmark Detection Pose-Invariant Pose-Invariant Face Alignment with a … 2017-07-19
Facial Landmark Detection CFSS Face Alignment Across Large Poses: … 2015-11-23
Facial Landmark Detection 3DDFA Face Alignment Across Large Poses: … 2015-11-23

Research Papers

Recent papers with results on this dataset: