TinaFace: Strong but Simple Baseline for Face Detection
arXiv:2011.13183
Abstract
Face detection has received intensive attention in recent years. Many works present lots of special methods for face detection from different perspectives like model architecture, data augmentation, label assignment and etc., which make the overall algorithm and system become more and more complex. In this paper, we point out that \textbf{there is no gap between face detection and generic object detection}. Then we provide a strong but simple baseline method to deal with face detection named TinaFace. We use ResNet-50 \cite{he2016deep} as backbone, and all modules and techniques in TinaFace are constructed on existing modules, easily implemented and based on generic object detection. On the hard test set of the most popular and challenging face detection benchmark WIDER FACE \cite{yang2016wider}, with single-model and single-scale, our TinaFace achieves 92.1\% average precision (AP), which exceeds most of the recent face detectors with larger backbone. And after using test time augmentation (TTA), our TinaFace outperforms the current state-of-the-art method and achieves 92.4\% AP. The code will be available at \url{https://github.com/Media-Smart/vedadet}.
References in corpus (13)
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- RetinaFace: Single-stage Dense Face Localisation in the Wild
- Face Attention Network: An Effective Face Detector for the Occluded Faces
- Face Detection through Scale-Friendly Deep Convolutional Networks
- Detecting Faces Using Region-based Fully Convolutional Networks
- PyramidBox++: High Performance Detector for Finding Tiny Face
- EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse
- Improved Selective Refinement Network for Face Detection
- Accurate Face Detection for High Performance
- Robust and High Performance Face Detector
- MaskFace: multi-task face and landmark detector
- Face Detection with Feature Pyramids and Landmarks