Pinned Repositories
3DmFV-Net
Point cloud classification in Real-time using 3DmFV representation and CNNs
CSF
LiDAR point cloud ground filtering / segmentation (bare earth extraction) method based on cloth simulation
d2l-zh
《动手学深度学习》：面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论”教材。
dfn
dgcnn
Dive-into-DL-PyTorch
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
Dive-into-DL-TensorFlow2.0
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的同意
earthengine-api
Python and JavaScript bindings for calling the Earth Engine API.
EllipseFit
Ellipse Fitting
farthest-point-sampling
A vanilla implementation of farthest point sampling (FPS) algorithm in paper: "The farthest point strategy for progressive image sampling"
JacksonY1's Repositories
JacksonY1/3DmFV-Net
Point cloud classification in Real-time using 3DmFV representation and CNNs
JacksonY1/CSF
LiDAR point cloud ground filtering / segmentation (bare earth extraction) method based on cloth simulation
JacksonY1/d2l-zh
《动手学深度学习》：面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论”教材。
JacksonY1/dfn
JacksonY1/dgcnn
JacksonY1/Dive-into-DL-PyTorch
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
JacksonY1/Dive-into-DL-TensorFlow2.0
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的同意
JacksonY1/earthengine-api
Python and JavaScript bindings for calling the Earth Engine API.
JacksonY1/EllipseFit
Ellipse Fitting
JacksonY1/farthest-point-sampling
A vanilla implementation of farthest point sampling (FPS) algorithm in paper: "The farthest point strategy for progressive image sampling"
JacksonY1/JacksonY1.github.io
This is Jason's personal website
JacksonY1/JAVA
存放JAVA开发的设计**、算法：《剑指Offer》、《编程珠玑》、《深入理解Java虚拟机：JVM高级特性与最佳实践》、《重构-改善既有代码的设计 中文版》、《clean_code(中文完整版)》、《Java编程**(第4版)》、《Java核心技术 卷I (第8版)》、《Quartz_Job+Scheduling_Framework》；一些大的上传不上来的文件在README
JacksonY1/KPConv
Kernel Point Convolutions
JacksonY1/Lane_Detection-An_Instance_Segmentation_Approach
A PyTorch implementation of the paper《Towards End-to-End Lane Detection: an Instance Segmentation Approach》
JacksonY1/micmac
Free open-source photogrammetry software tools
JacksonY1/PCV
Open source Python module for computer vision
JacksonY1/point_labeler
My awesome point cloud labeling tool
JacksonY1/pointnet2
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
JacksonY1/pointSIFT
a module for 3D semantic segmentation in point clouds.
JacksonY1/polygon-clipping
you can do anything you want to achieve your goal
JacksonY1/practice
here is a dirty hand test
JacksonY1/REKCARC-TSC-UHT
清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University
JacksonY1/RSNet
This is the official implementation of RSNet.
JacksonY1/SCNN
Spatial CNN for traffic lane detection (AAAI2018)
JacksonY1/SSL4EO-S12
SSL4EO-S12: a large-scale dataset for self-supervised learning in Earth observation
JacksonY1/Supervoxel-for-3D-point-clouds
A no dependency, header-only, license free, fast supervoxel segmentation library for 3D point clouds
JacksonY1/time-push
JacksonY1/torchgeo
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
JacksonY1/VPGNet
VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition (ICCV 2017)
JacksonY1/weixin_tuisong
基于猪咪不是猪老哥制作的微信公众号推送教程