Face Detection
133 papers with code • 13 benchmarks • 36 datasets
Face Detection is a computer vision task that involves automatically identifying and locating human faces within digital images or videos. It is a fundamental technology that underpins many applications such as face recognition, face tracking, and facial analysis.
( Image credit: insightface )
Benchmarks
These leaderboards are used to track progress in Face Detection
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Libraries
Use these libraries to find Face Detection models and implementations
ADE20K
Manga109
FDDB
AFW
UMDFaces
PASCAL Face
COCO-WholeBody
WIDER
MALF
Most implemented papers
PyramidBox++: High Performance Detector for Finding Tiny Face
code-implementation1/Code6
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With the rapid development of deep convolutional neural network, face detection has made great progress in recent years.
Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation
Li-Chongyi/Zero-DCE_extension
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This paper presents a novel method, Zero-Reference Deep Curve Estimation (Zero-DCE), which formulates light enhancement as a task of image-specific curve estimation with a deep network.
Multi-view Face Detection Using Deep Convolutional Neural Networks
In this paper we propose Deep Dense Face Detector (DDFD), a method that does not require pose/landmark annotation and is able to detect faces in a wide range of orientations using a single model based on deep convolutional neural networks.
Manga FaceNet
Among various elements of manga, character’s face plays one of the most important role in access and retrieval.
S$^3$FD: Single Shot Scale-invariant Face Detector
This paper presents a real-time face detector, named Single Shot Scale-invariant Face Detector (S$^3$FD), which performs superiorly on various scales of faces with a single deep neural network, especially for small faces.
Selective Refinement Network for High Performance Face Detection
ChiCheng123/SRN
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In particular, the SRN consists of two modules: the Selective Two-step Classification (STC) module and the Selective Two-step Regression (STR) module.
VarGFaceNet: An Efficient Variable Group Convolutional Neural Network for Lightweight Face Recognition
To improve the discriminative and generalization ability of lightweight network for face recognition, we propose an efficient variable group convolutional network called VarGFaceNet.
Masked Face Recognition Dataset and Application
These datasets are freely available to industry and academia, based on which various applications on masked faces can be developed.
MaskedFace-Net -- A Dataset of Correctly/Incorrectly Masked Face Images in the Context of COVID-19
However, at the moment, there are no available large dataset of masked face images that permits to check if detected masked faces are correctly worn or not.
Low-Light Image and Video Enhancement Using Deep Learning: A Survey
Li-Chongyi/Lighting-the-Darkness-in-the-Deep-Learning-Era-Open
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Low-light image enhancement (LLIE) aims at improving the perception or interpretability of an image captured in an environment with poor illumination.
