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ai-paper-drawer

人工智能论文关键点集结。This project aims to collect key points of AI papers.

ai-paper-notes

ai-power

AI动力(AI Power) GPU云平台使用指南

awesome-point-cloud-analysis

A list of papers and datasets about point cloud analysis (processing)

deepe_nocor_pytorch

Estimate the essential matrix from two input images following the paper Deep Fundamental Matrix Estimation without Correspondences

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

geo-cnn-pytorch-pyg

A Pytorch Implementation of “Modeling Local Geometric Structure of 3D Point Clouds using Geo-CNN”

machine-learning-notebook

A PC program that provides one AI note per day to help accumulate AI knowledge

miao-a-songhao-advanced-mathematics-notes

宋浩老师《高等数学》同济版 网课笔记

miao-a-songhao-linear-algebra-notes

宋浩老师“惊叹号”系列《线性代数》网课笔记及时间点目录 Song hao "exclamation mark" series "linear algebra" course notes and time point directory

miao-a-songhao-probability-theory-notes

my-favorite-ai-papers

oanet

Implementation of ICCV19 Paper "Learning Two-View Correspondences and Geometry Using Order-Aware Network"

point-cloud-papers

pointcloudwork

Point Cloud Work

pointnet2_pytorch

PointNet and PointNet++ implemented by pytorch (no tf_opt)

python-algorithm-formula

基于Python的算法题公式化套路总结

pytorch-common-template

Storing functions commonly used in training pytorch models

pytorch-perceptual-losses-style-transfer-attention-capsule-network

Pytorch - Perceptual Losses - Style Transfer - Attention Capsule Network

pytorch-rotationnet

pytorch_geometric

Geometric Deep Learning Extension Library for PyTorch

relearn-linear-algebra

shortest-leetcode-python-solutions

Leet Code 刷题笔记 - - 不求最快最省，但求最短最优雅，Shorter is better here.

simplest-leetcode-cpp-solutions

C++ 极简之路，用繁琐的语言做简单的事。Exploring the simplest and deepest way of Cpp.

superglue_superpoint_megadepth

supergluepretrainednetwork

SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)

torch-vectorized

Fast analytical implementation of batch eigen-decomposition for 3x3 symmetric matrices with Pytorch. > 250x faster than regular Pytorch implementation of batch eigen-decomposition.