Face detection is the task of detecting faces in a photo or video (and distinguishing them from other objects).
( Image credit: FaceBoxes )
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We describe a method for visual object detection based on an ensemble of optimized decision trees organized in a cascade of rejectors.
Under the new schema, the proposed method can achieve superior accuracy (WIDER FACE Val/Test -- Easy: 0. 910/0. 896, Medium: 0. 881/0. 865, Hard: 0. 780/0. 770; FDDB -- discontinuous: 0. 973, continuous: 0. 724).
Ranked #6 on Face Detection on FDDB
Face detection and alignment in unconstrained environment are challenging due to various poses, illuminations and occlusions.
Ranked #14 on Face Detection on WIDER Face (Easy)
Face detection and alignment in unconstrained environment is always deployed on edge devices which have limited memory storage and low computing power.
The MSCL aims at enriching the receptive fields and discretizing anchors over different layers to handle faces of various scales.
Ranked #4 on Face Detection on PASCAL Face
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.
Ranked #2 on Face Detection on Annotated Faces in the Wild