Pinned Repositories
alpr-unconstrained
License Plate Detection and Recognition in Unconstrained Scenarios
buildOpenCVTX2
Build and install OpenCV for the NVIDIA Jetson TX2
caffe
Caffe: a fast open framework for deep learning.
CrowdCountingCVPR18
The rep for the Crowd Counting paper accepted by CVPR 2018
CSRNet
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
CSRNet-caffe
CSRNet train and test on caffe
ECO
c++ visual studio implement of ECO: Efficient Convolution Operators for Tracking
light-weight-refinenet
Light-Weight RefineNet for Real-Time Semantic Segmentation
OpenTracker
Real-time C++ ECO tracker etc. speed-up by SSE/NEON, support Linux, Mac, Jetson TX1/2, raspberry pi
ou-zhi-hui's Repositories
ou-zhi-hui/OpenTracker
Real-time C++ ECO tracker etc. speed-up by SSE/NEON, support Linux, Mac, Jetson TX1/2, raspberry pi
ou-zhi-hui/CSRNet-caffe
CSRNet train and test on caffe
ou-zhi-hui/ECO
c++ visual studio implement of ECO: Efficient Convolution Operators for Tracking
ou-zhi-hui/CSRNet
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
ou-zhi-hui/light-weight-refinenet
Light-Weight RefineNet for Real-Time Semantic Segmentation
ou-zhi-hui/alpr-unconstrained
License Plate Detection and Recognition in Unconstrained Scenarios
ou-zhi-hui/buildOpenCVTX2
Build and install OpenCV for the NVIDIA Jetson TX2
ou-zhi-hui/caffe
Caffe: a fast open framework for deep learning.
ou-zhi-hui/CrowdCountingCVPR18
The rep for the Crowd Counting paper accepted by CVPR 2018
ou-zhi-hui/deep_learning_object_detection
A paper list of object detection using deep learning.
ou-zhi-hui/deeplab_v2
基于v2版本的deeplab,使用VGG16模型，在VOC2012，Pascal-context，NYU-v2等多个数据集上进行训练
ou-zhi-hui/Deeplab_v2_test
Deeplab_V2demo测试
ou-zhi-hui/deeplab_v3
Tensorflow Implementation of the Semantic Segmentation DeepLab_V3 CNN
ou-zhi-hui/DeepLabv3_MobileNetv2_PyTorch
A PyTorch Implementation of MobileNetv2+DeepLabv3
ou-zhi-hui/License-Plate-Detect-Recognition-via-Deep-Neural-Networks-accuracy-up-to-99.9
works in real-time with detection and recognition accuracy up to 99.8% for Chinese license plates: 100 ms/plate
ou-zhi-hui/mlhub123
机器学习&深度学习网站资源汇总（Machine Learning Resources）
ou-zhi-hui/opencv
Open Source Computer Vision Library