Zhongen Li's repositories
3D-Machine-Learning
A resource repository for 3D machine learning
3D-point-capsule-networks
Perturbation experiments on the latent capsules of 3D Point Capsule Networks by Zhao et al.
A-SCN
Attentional ShapeContextNet for Point Cloud Recognition
aitom
AI for tomography
All-about-XAI
This repository is all about papers and tools of Explainable AI
awesome-gan-inversion
A collection of resources on GAN inversion.
awesome-point-cloud-analysis
A list of papers and datasets about point cloud analysis (processing)
awesome-tensorflow
TensorFlow - A curated list of dedicated resources http://tensorflow.org
belkin-energy-disaggregation
I will try to learn from this project
CNN-Attention
An Image Classifier with attention layers visualized
Complex-YOLOv4-Pytorch
The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"
curated-list-of-awesome-3D-Morphable-Model-software-and-data
The idea of this list is to collect shared data and algorithms around 3D Morphable Models. You are invited to contribute to this list by adding a pull request. The original list arised from the Dagstuhl seminar on 3D Morphable Models https://www.dagstuhl.de/19102 in March 2019.
DR-Learning-for-3D-Face
Implementation for paper "Disentangled Representation Learning for 3D Face Shape" CVPR 2019
Enable-HiDPI-OSX
Enable HiDPI on OS X
hello-world
trial
InfoGAN
InfoGAN Implementation in PyTorch
interpretability-by-parts
Code repository for "Interpretable and Accurate Fine-grained Recognition via Region Grouping", CVPR 2020 (Oral)
KITTI-Dataset
Examination of the KITTI dataset.
learnGitBranching
An interactive git visualization and tutorial. Aspiring students of git can use this app to educate and challenge themselves towards mastery of git!
librealsense
Intel® RealSense™ SDK
Lihang
Statistical learning methods, 统计学习方法(第2版)[李航] [笔记, 代码, notebook, 参考文献, Errata, lihang]
MachineLearning-DeepLearning-NLP-LeetCode-StatisticalLearningMethod-TensorFlow
最近在学习机器学习，深度学习，自然语言处理，统计学习方法等知识，理论学习主要根据readme的链接，在学习理论的同时，决定自己将学习的相关算法用Python实现一遍，并结合GitHub上相关大牛的代码进行改进，本项目会不断的更新相关算法，欢迎star，fork和关注。 主要包括： 1.吴恩达Andrew Ng老师的机器学习课程作业个人笔记 Python实现， 2.deeplearning.ai（吴恩达老师的深度学习课程笔记及资源） Python实现， 3.李航《统计学习方法》 Python代码实现， 4.自然语言处理NLP 牛津大学xDeepMind Python代码实现， 5.LeetCode刷题，题析，分析心得笔记 Java和Python代码实现， 6.TensorFlow人工智能实践代码笔记 北京大学曹健老师课程和TensorFlow：实战Google深度学习框架（第二版） Python代码实现， 附带一些个人心得和笔记。GitHub上有很多机器学习课程的代码资源，我也准备自己实现一下，后续会更新笔记，代码和百度云网盘链接。 这个项目主要是学习算法的，并且会不断更新相关资源和代码，欢迎关注，star，fork！ Min's blog 欢迎访问我的博客主页！ (Welcome to my blog website !)https://liweimin1996.github.io/
models
Models and examples built with TensorFlow
Non-Maximum-Suppression
描述非极大值抑制（Non-Maximum-Suppression，NMS）
pointcloud_experiments
Experiments with Pointnet and GAPNet/GAPointNet. Attention and transformers for point clouds.
Shape-Measure
PyTorch version of shape evaluation metrics
StarMap
StarMap for Category-Agnostic Keypoint and Viewpoint Estimation