106 papers with code • 7 benchmarks • 37 datasets
Face detection is the task of detecting faces in a photo or video (and distinguishing them from other objects).
( Image credit: insightface )
Face detection and alignment in unconstrained environment are challenging due to various poses, illuminations and occlusions.
In this paper we propose an implement a general convolutional neural network (CNN) building framework for designing real-time CNNs.
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).
The 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.
We describe a method for visual object detection based on an ensemble of optimized decision trees organized in a cascade of rejectors.
The MSCL aims at enriching the receptive fields and discretizing anchors over different layers to handle faces of various scales.