zuoqing1988 / train-ssd
train ssd
☆10Updated 5 years ago
Alternatives and similar repositories for train-ssd:
Users that are interested in train-ssd are comparing it to the libraries listed below
- train Gender and Age☆39Updated 6 years ago
- fast face detector☆18Updated 6 years ago
- Small library for working with rotated rectangle shaped image regions.☆16Updated 7 years ago
- MNN Implementation of the paper of LFFD: A Light and Fast Face Detector for Edge Devices☆128Updated 5 years ago
- MobileNet-SSD Face Detection by ncnn☆21Updated 6 years ago
- A Gluon implement of MobileNetV3☆28Updated 5 years ago
- 集成了好几个版本的caffe☆22Updated 6 years ago
- PCN based on ncnn framework.☆81Updated 6 years ago
- An MTCNN based face detection and an optical-flow based tracking running in two threads.☆35Updated 6 years ago
- tensorRT retinaface mobilenet☆42Updated 5 years ago
- ☆30Updated 5 years ago
- Intel OpenVINO Implementation of the paper of LFFD: A Light and Fast Face Detector for Edge Devices☆45Updated 5 years ago
- FaceBoxes: A CPU Real-time Face Detector with High Accuracy☆85Updated 7 years ago
- mtcnn-light version of adaptive image size☆47Updated 6 years ago
- Support most of operator which convert mxnet to caffe.☆60Updated 5 years ago
- Retinaface caffe with mnetv2 0.25(and many more)☆57Updated 5 years ago
- 用pytorch训练ssd,相比原版pytorch-ssd改动了不少☆11Updated 2 years ago
- A C++ API of the LFFD with ncnn☆99Updated 4 years ago
- train Snet(by thundernet) in imagenet☆18Updated 5 years ago
- ☆16Updated 5 years ago
- Based on Onet to stabilize Face Detection BoundingBox. Fast, Smooth.☆61Updated 2 years ago
- A re-implementation of PFLD, https://arxiv.org/abs/1902.10859☆45Updated 5 years ago
- A caffe implementation of Mnasnet: MnasNet: Platform-Aware Neural Architecture Search for Mobile.☆52Updated 6 years ago
- ☆128Updated 6 years ago
- reproduce faceboxes☆53Updated 6 years ago
- It is a mtcnn project based on ncnn☆90Updated 7 years ago
- Windows version for Single Stage Headless Face Detector☆10Updated 7 years ago
- Android 版本MTCNN Landmark 106, ncnn优化☆37Updated 5 years ago
- train mxnet unet, then run it in ncnn☆63Updated 6 years ago
- 移动端快速人脸检测模型是基于RetinaFace的优化去掉stride8以及stride32和stride16的landmark 在CPU位Intel(R) Pentium(R) CPU G2020 @ 2.90GHz(2900 MHz)的设备中人脸检测可达到40ms/帧☆15Updated 5 years ago