# Face Attention Network: An Effective Face Detector for the Occluded Faces

arXiv: https://arxiv.org/abs/1711.07246 · HTML: https://mlsanity.com/paper/1711.07246/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Nov 2017.

## Built on by (most cited first, 19 of 19)

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- [YOLO-FaceV2: A Scale and Occlusion Aware Face Detector](https://mlsanity.com/paper/2208.02019/) (2022)
- [Detection of a facemask in real-time using deep learning methods: Prevention of Covid 19](https://mlsanity.com/paper/2401.15675/) (2024)
- [MogFace: Towards a Deeper Appreciation on Face Detection](https://mlsanity.com/paper/2103.11139/) (2021)
- [GEFF: Improving Any Clothes-Changing Person ReID Model using Gallery Enrichment with Face Features](https://mlsanity.com/paper/2211.13807/) (2022)
- [A Survey on Masked Facial Detection Methods and Datasets for Fighting Against COVID-19](https://mlsanity.com/paper/2201.04777/) (2022)
- [Bias-Aware Face Mask Detection Dataset](https://mlsanity.com/paper/2211.01207/) (2022)
- [EfficientFace: An Efficient Deep Network with Feature Enhancement for Accurate Face Detection](https://mlsanity.com/paper/2302.11816/) (2023)
- [Effectiveness of Detection-based and Regression-based Approaches for Estimating Mask-Wearing Ratio](https://mlsanity.com/paper/2111.12888/) (2021)
- [FaceTracer: Unveiling Source Identities from Swapped Face Images and Videos for Fraud Prevention](https://mlsanity.com/paper/2412.08082/) (2024)
- [MaskMTL: Attribute prediction in masked facial images with deep multitask learning](https://mlsanity.com/paper/2201.03002/) (2022)
- [A Diver Attention Estimation Framework for Effective Underwater Human-Robot Interaction](https://mlsanity.com/paper/2209.14447/) (2022)
- [A Comparative Study of Face Detection Algorithms for Masked Face Detection](https://mlsanity.com/paper/2305.11077/) (2023)
- [A Lightweight and Accurate Face Detection Algorithm Based on Retinaface](https://mlsanity.com/paper/2308.04340/) (2023)
- [YOLOv11-Litchi: Efficient Litchi Fruit Detection based on UAV-Captured Agricultural Imagery in Complex Orchard Environments](https://mlsanity.com/paper/2510.10141/) (2025)
- [PixReenact: Pixel-Conditioned Causal Video Diffusion for Streaming Head-Avatar Reenactment](https://mlsanity.com/paper/2610.05233/) (2026)
- [Weave Mamba Fusion: Global Cross-Scale Interaction for Lightweight Face Detection](https://mlsanity.com/paper/2610.05865/) (2026)

## Abstract (arXiv)

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.