Puguang Cai's repositories
C-learning
C++ Learning record
adminForTrain
java project
C-3-Framework
An open-source PyTorch code for crowd counting
DataStructure
Data structure learning&The Code
Stereo-matching-python
Python implementation of various stereo matching algorithms.
dotnets
Create simple drawings of neural networks using graphviz
fire-smoke-detect-yolov4
fire-smoke-detect-yolov4-yolov5 and fire-smoke-detection-dataset 火灾检测,烟雾检测
lanenet-lane-detection
Unofficial implemention of lanenet model for real time lane detection using deep neural network model https://maybeshewill-cv.github.io/lanenet-lane-detection/
Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
mmdetection
OpenMMLab Detection Toolbox and Benchmark
OpenCV-Python-Tutorial
📖 OpenCV-Python image processing tutorial for beginners
Paddle
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
Puguang-Cai
蔡普光的个人主页
Solar_Wind
Prediction of solar wind.
TDAM
Implementation code for the paper "Solar Wind Speed Prediction With Two-Dimensional Attention Mechanism"
tinynn
A lightweight deep learning library
UniPose
We propose UniPose, a unified framework for human pose estimation, based on our “Waterfall” Atrous Spatial Pooling architecture, that achieves state-of-art-results on several pose estimation metrics. Current pose estimation methods utilizing standard CNN architectures heavily rely on statistical postprocessing or predefined anchor poses for joint localization. UniPose incorporates contextual seg- mentation and joint localization to estimate the human pose in a single stage, with high accuracy, without relying on statistical postprocessing methods. The Waterfall module in UniPose leverages the efficiency of progressive filter- ing in the cascade architecture, while maintaining multi- scale fields-of-view comparable to spatial pyramid config- urations. Additionally, our method is extended to UniPose- LSTM for multi-frame processing and achieves state-of-the- art results for temporal pose estimation in Video. Our re- sults on multiple datasets demonstrate that UniPose, with a ResNet backbone and Waterfall module, is a robust and efficient architecture for pose estimation obtaining state-of- the-art results in single person pose detection for both sin- gle images and videos.