JingX's repositories
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scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
100-Days-of-ML-Code-Chinese-Version
Chinese Translation for Machine Learning Infographics
3DOD_thesis
3D Object Detection for Autonomous Driving in PyTorch, trained on the KITTI dataset.
arl-eegmodels
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
Bert-TextClassification
Implemention some Baseline Model upon Bert for Text Classification
DLInterview
Deep Learning Interview 深度学习面试题目汇总
frustum-pointnets
Frustum PointNets for 3D Object Detection from RGB-D Data
glqblog
my blog
Interview-Notebook
:books: 技术面试需要掌握的基础知识整理，欢迎编辑~
KITTI-Dataset
Examination of the KITTI dataset.
LeetCode
:pencil: Python / C++ 11 Solutions of All LeetCode Questions
machine-learning-notes
This is the notes of the way of machine learning study. You may find something useful in it.
Open3D-PointNet2-Semantic3D
Semantic3D segmentation with Open3D and PointNet++
Skill-Tree
🐼 准备秋招，欢迎来树上取果实
SNIPER
SNIPER / AutoFocus is an efficient multi-scale object detection training / inference algorithm
spherical-projection
Create RGB point cloud from KITTI raw data, project it to 2D representation
SqueezeSegV2
Implementation of SqueezeSegV2, Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud
Stereo-RCNN
Code for 'Stereo R-CNN based 3D Object Detection for Autonomous Driving' (CVPR 2019)