Open-source alternatives to Faceboxes

This repository includes the code for training and evaluating the SSH face detector introduced in our ICCV 2017 paper.

A minimalistic framework for real-time object detection (with a pre-trained face detector)

PaddlePaddle 提供了丰富的计算单元，使得用户可以采用模块化的方法解决各种学习问题。在此Repo中，我们展示了如何用 PaddlePaddle来解决常见的机器学习任务，提供若干种不同的易学易用的神经网络模型。PaddlePaddle用户可领取免费Tesla V100在线算力资源，高效训练模型，每日登陆即送12小时，连续五天运行再加送48小时，前往使用免费算力。

By Peiyun Hu and Deva Ramanan at Carnegie Mellon University.

SeetaFaceEngine is a C++ face recognition engine designed to detect, align, and identify human faces. It functions as a native library that performs facial analysis without relying on external third-party software libraries. The system utilizes a convolutional neural network framework for facial feature extraction and identity matching, representing identities as numerical feature-vector embeddings. It employs a funnel-structured cascade schema for real-time face localization and stacked auto-encoder networks to normalize facial orientation through landmark alignment. The toolkit integrates

By Shifeng Zhang

This repository includes the training and evaluating codes for SFA face detector, implemented in pycaffe. The SFA codes is an extension of the SSH repository. Our method is trained on the training set of the WIDER FACE dataset. If it is useful, please light up a star for this repository.

libfacedetection is a C++ face detection library and computer vision tool. It utilizes a neural network face detector to identify human faces in images and return bounding box coordinates. The library is designed for low latency and high throughput processing, enabling real-time face detection in image and video streams. It supports automated image analysis for identifying coordinates of human faces across large batches of photos and high-performance video processing.

see details at https://github.com/Tencent/FaceDetection-DSFD

The C++ implementation of A Fast and Accurate Unconstrained Face Detector.

Link to the trained model