mlsanityData to 14 Oct 2026

WIDER FACE: A Face Detection Benchmark

arXiv 1511.06523 ↗First posted 20 Nov 2015cs.CVcited by 298

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Abstract (arXiv)

Face detection is one of the most studied topics in the computer vision community. Much of the progresses have been made by the availability of face detection benchmark datasets. We show that there is a gap between current face detection performance and the real world requirements. To facilitate future face detection research, we introduce the WIDER FACE dataset, which is 10 times larger than existing datasets. The dataset contains rich annotations, including occlusions, poses, event categories, and face bounding boxes. Faces in the proposed dataset are extremely challenging due to large variations in scale, pose and occlusion, as shown in Fig. 1. Furthermore, we show that WIDER FACE dataset is an effective training source for face detection. We benchmark several representative detection systems, providing an overview of state-of-the-art performance and propose a solution to deal with large scale variation. Finally, we discuss common failure cases that worth to be further investigated. Dataset can be downloaded at: mmlab.ie.cuhk.edu.hk/projects/WIDERFace

Key facts. Cited by 298 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Nov 2015.

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Citing papers per year: 2021: 76; 2022: 60; 2023: 47; 2024: 55; 2025: 35; 2026: 25.

298 papers.

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  10. 2021Sample and Computation Redistribution for Efficient Face Detectioncited by 89
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  12. 2023DR2: Diffusion-based Robust Degradation Remover for Blind Face Restorationcited by 79
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