Corpus ID: 29125845

Multi-Branch Fully Convolutional Network for Face Detection

@article{Bai2017MultiBranchFC,
  title={Multi-Branch Fully Convolutional Network for Face Detection},
  author={Yancheng Bai and Bernard Ghanem},
  journal={ArXiv},
  year={2017},
  volume={abs/1707.06330}
}
Face detection is a fundamental problem in computer vision. It is still a challenging task in unconstrained conditions due to significant variations in scale, pose, expressions, and occlusion. In this paper, we propose a multi-branch fully convolutional network (MB-FCN) for face detection, which considers both efficiency and effectiveness in the design process. Our MB-FCN detector can deal with faces at all scale ranges with only a single pass through the backbone network. As such, our MB-FCN… Expand
Finding Tiny Faces in the Wild with Generative Adversarial Network
Detecting small faces in the wild based on generative adversarial network and contextual information
Multi-task Generative Adversarial Network for Detecting Small Objects in the Wild

References

SHOWING 1-10 OF 42 REFERENCES
Multi-view Face Detection Using Deep Convolutional Neural Networks
A convolutional neural network cascade for face detection
Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks
From Facial Parts Responses to Face Detection: A Deep Learning Approach
CMS-RCNN: Contextual Multi-Scale Region-based CNN for Unconstrained Face Detection
Supervised Transformer Network for Efficient Face Detection
WIDER FACE: A Face Detection Benchmark
Aggregate channel features for multi-view face detection
Face Detection with the Faster R-CNN
R-FCN: Object Detection via Region-based Fully Convolutional Networks
...
1
2
3
4
5
...