FlashNet: A Real-time Anchor-Free Face Detector

Due to the limitation of computational cost, one of the remaining open challenges in face detection is designing an efficient face detector for mobile platforms. Some of the previous methods obtain superior performance on the WIDER FACE benchmark, but they are computationally unfriendly for mobile devices with limited computing power and memory resource. Inspired by recent anchor-free detection methods, we propose a lightweight anchor-free face detector named FlashNet, which is built with only 150k parameters. Comprehensive and extensive experiments conducted on popular benchmarks show that the proposed lightweight face detector achieves impressive detection accuracy(78.87% AP on WIDER FACE hard validation set and 97.30% TPR discontinuous score on FDDB). Without bells and whistles, the proposed lightweight detector can achieve impressive runtime efficiency that outperforms existing methods by a large margin. Our method achieves 163.93 FPS on NVIDIA TX2 GPU and 30.51 FPS on NVIDIA TX2 CPU at VGA resolution, separately.