Face Attention Network: An Effective Face Detector for the Occluded Faces
The performance of face detection has been largely improved with the development of convolutional neural network. However, the occlusion issue due to mask and sunglasses, is still a challenging problem. The improvement on the recall of these occluded cases usually brings the risk of high false positives. In this paper, we present a novel face detector called Face Attention Network (FAN), which can significantly improve the recall of the face detection problem in the occluded case without compromising the speed. More specifically, we propose a new anchor-level attention, which will highlight the features from the face region. Integrated with our anchor assign strategy and data augmentation techniques, we obtain state-of-art results on public face detection benchmarks like WiderFace and MAFA. The code will be released for reproduction.
Code (1)
Tasks
Data AugmentationFace DetectionOccluded Face DetectionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Adversarial Occlusion-aware Face Detection
Occluded face detection is a challenging detection task due to the large appearance variations incurred by various real-world occlusions. This paper introduces an Adversarial Occlusion-aware Face Detector (AOFD) by simul…
Face DetectionOccluded Face DetectionA Comparative Study of Face Detection Algorithms for Masked Face Detection
Contemporary face detection algorithms have to deal with many challenges such as variations in pose, illumination, and scale. A subclass of the face detection problem that has recently gained increasing attention is occl…
Face DetectionOccluded Face DetectionEnd2End Occluded Face Recognition by Masking Corrupted Features
With the recent advancement of deep convolutional neural networks, significant progress has been made in general face recognition. However, the state-of-the-art general face recognition models do not generalize well to o…
Face RecognitionAttention-based Partial Face Recognition
Photos of faces captured in unconstrained environments, such as large crowds, still constitute challenges for current face recognition approaches as often faces are occluded by objects or people in the foreground. Howeve…
Face RecognitionGrid Loss: Detecting Occluded Faces
Detection of partially occluded objects is a challenging computer vision problem. Standard Convolutional Neural Network (CNN) detectors fail if parts of the detection window are occluded, since not every sub-part of the …
Face Detection