dayeren / Computer-VisionLinks
☆18Updated 8 years ago
Alternatives and similar repositories for Computer-Vision
Users that are interested in Computer-Vision are comparing it to the libraries listed below
Sorting:
- Awesome Caffe☆219Updated 5 years ago
- use mxnet to train your own data with just oneclick☆79Updated 7 years ago
- The code to learn mxnet☆60Updated 8 years ago
- Latex: translate the book practical python and opencv to Chinese☆86Updated 7 years ago
- ☆74Updated 7 years ago
- SSD-based plate detection☆122Updated 7 years ago
- Using adaboost to detect carface☆22Updated 9 years ago
- Caffe's usage☆33Updated 4 years ago
- This project is about the utilization of CNN to detect human face point. Trained with the dataset LFW and images from Internet.☆45Updated 9 years ago
- Image retrieval system demo based on caffe and lsh☆73Updated 9 years ago
- Face image rerieval☆90Updated 7 years ago
- ☆46Updated 9 years ago
- Usage of https://github.com/davidsandberg/facenet/ model for people identification☆65Updated 7 years ago
- Small and easy C++ AdaBoost Implementation☆70Updated 14 years ago
- Classify Traffic Signs.☆29Updated 8 years ago
- Best practice of computer vision learning☆39Updated 4 years ago
- DeepLearningBook 读书会笔记及讲义☆146Updated 8 years ago
- C++ detect and train of "A Fast and Accurate Unconstrained Face Detector".☆125Updated 7 years ago
- ☆48Updated 9 years ago
- caffecn_master☆30Updated 8 years ago
- Learning Deep Learning☆23Updated 8 years ago
- train model of "A Lightened CNN for Deep Face Representation" 人脸识别☆118Updated 7 years ago
- My implementation of high dimensional LBP feature for face recognition☆104Updated 8 years ago
- Pedestrian detection☆50Updated 9 years ago
- This code is an implementation of a trained YOLO neural network used with the TensorRT framework.☆88Updated 8 years ago
- a C++ wrapper of Caffe and mxnet to make predictions☆49Updated 7 years ago
- YOLO VS2015 c++ code, Only need opencv, do not rely on the Caffe Library☆47Updated 7 years ago
- Version control for my deep learning course.☆47Updated 7 years ago
- Caffe☆97Updated 10 years ago
- This is re-implementation of "ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices"☆158Updated 7 years ago