Pinned Repositories
anomaly-detection-resources
Anomaly detection related books, papers, videos, and toolboxes
awesome-image-classification
A curated list of deep learning image classification papers and codes，forked on 2019/4/18.
awesome-semantic-segmentation
:metal: awesome-semantic-segmentation,forked on 2019/4/18.
berkeley-stat-157
Homepage for STAT 157 at UC Berkeley
caffe
Caffe: a fast open framework for deep learning.forked on 2018/7/15.
caffe-model
Caffe models (including classification, detection and segmentation) and deploy files for famouse networks
caffe-model-zoo
caffe pretrained models and prototxt
DataAugmentationForObjectDetection
Data Augmentation For Object Detection
deep_learning_object_detection
A paper list of object detection using deep learning，forked on 2019/4/18.
HigherHRNet-Human-Pose-Estimation
This is an official implementation of our CVPR 2020 paper "HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation" (https://arxiv.org/abs/1908.10357)
liangshaohua's Repositories
liangshaohua/HigherHRNet-Human-Pose-Estimation
This is an official implementation of our CVPR 2020 paper "HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation" (https://arxiv.org/abs/1908.10357)
liangshaohua/berkeley-stat-157
Homepage for STAT 157 at UC Berkeley
liangshaohua/DDRNet.pytorch
This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data
liangshaohua/DDRNet.Pytorch-1
liangshaohua/DDRNet.TensorRT
TensorRT of DDRNet for real-time segmentation
liangshaohua/deep-high-resolution-net.pytorch
The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"
liangshaohua/DeepLearningExamples
Deep Learning Examples
liangshaohua/DETA
Detection Transformers with Assignment
liangshaohua/EasyLogger
A ultra-lightweight(ROM<1.6K, RAM<0.3k), high-performance C/C++ log library. | 一款超轻量级(ROM<1.6K, RAM<0.3k)、高性能的 C/C++ 日志库
liangshaohua/gh-proxy
github release、archive以及项目文件的加速项目
liangshaohua/ghostnet.pytorch
73.6% GhostNet 1.0x pre-trained model on ImageNet
liangshaohua/medicaldetectiontoolkit
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
liangshaohua/mmdetection-mini
mmdetection最小学习版
liangshaohua/numpy-ml
Machine learning, in numpy
liangshaohua/ObjectDetection-OneStageDet
单阶段通用目标检测器
liangshaohua/PaddleOCR
Awesome multilingual OCR toolkits based on PaddlePaddle （practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices）
liangshaohua/pytorch-cnn-visualizations
Pytorch implementation of convolutional neural network visualization techniques
liangshaohua/pytorch-YOLOv4
PyTorch ,ONNX and TensorRT implementation of YOLOv4
liangshaohua/PyTorch_YOLOv4
PyTorch implementation of YOLOv4
liangshaohua/ScaledYOLOv4
liangshaohua/tutorials
PyTorch tutorials.
liangshaohua/UVO_Challenge
liangshaohua/win10_yolov5_tensorRT
vs2015上使用tensorRT加速yolov5推理（Using tensorrt to accelerate yolov5 reasoning on vs2015）
liangshaohua/YOLO-v5
:art: Pytorch YOLO v5 训练自己的数据集超详细教程！！！ :art: (提供PDF训练教程下载）
liangshaohua/yolov2-yolov3_PyTorch
liangshaohua/yolov3-channel-and-layer-pruning
yolov3 yolov4 channel and layer pruning, Knowledge Distillation 层剪枝，通道剪枝，知识蒸馏
liangshaohua/YOLOv3v4-ModelCompression-MultidatasetTraining-Multibackbone
YOLO ModelCompression MultidatasetTraining
liangshaohua/yolov5
YOLOv5 in PyTorch > ONNX > CoreML > iOS
liangshaohua/yolov5s_bdd100k
Train a yolo v5 object detection model on Bdd100k dataset
liangshaohua/YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported.