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100-days-of-ml-code

100-Days-Of-ML-Code中文版

3d_os

aml-homework3-da

cvpr2018-shape-completion

CVPR 2018 paper "Learning 3D Shape Completion from Laser Scan Data with Weak Supervision".

data-science-heart-disease-proj

deco

DeCo: Denoise and Contrast for Category Agnostic Shape Completion

depthcontrast

DepthContrast self-supervised learning for 3D

dgcnn

dgcnn.pytorch

A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)

differnet

This is the official repository to the WACV 2021 paper "Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows" by Marco Rudolph, Bastian Wandt and Bodo Rosenhahn.

diffpool

effectivepytorch

PyTorch tutorials and best practices.

etw_pytorch_utils

gacnet

Pytorch implementation of 'Graph Attention Convolution for Point Cloud Segmentation'

gicn

goingdeeperwpointnetworks

This project releases the code for the Paper "Going Deeper with Point Networks"

graph-based-deep-learning-literature

links to conference publications in graph-based deep learning

graph_attention_pool

Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)

jsenet

Implementation of ECCV2020 paper - JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds

kcnet

Code for "Mining Point Cloud Local Structures by Kernel Correlation and Graph Max Pooling", CVPR, 2018.

l2g

End-to-End Learning to Grasp from Object Point Clouds

learning3d

This is a complete package of recent deep learning methods for 3D point clouds in pytorch (with pretrained models).

mitsuba2pointcloudrenderer

rendering (optionally temporal) point clouds using Mitsuba2

msn-point-cloud-completion

Morphing and Sampling Network for Dense Point Cloud Completion (AAAI2020)

nopc

Pytorch implementation of Neural Opacity Point Cloud.

openselfsup

Self-Supervised Learning Toolbox and Benchmark

pcl2pcl-gan-pub

Unpaired Point Cloud Completion on Real Scans using Adversarial Training

pct_pytorch

Pytorch implementation of PCT: Point Cloud Transformer

point-transformer-pytorch

Implementation of the Point Transformer layer, in Pytorch

pointclouddatasets

3D point cloud datasets in HDF5 format, containing uniformly sampled 2048 points per shape.