Movatterモバイル変換


[0]ホーム

URL:


Skip to content

Navigation Menu

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Sign up

CVPR Paper - "3D Point Cloud Registration for Localization using a Deep Neural Network Auto-Encoder" - Partial Implementation Code

NotificationsYou must be signed in to change notification settings

gilbaz/LORAX

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 
 
 

Repository files navigation

CVPR Oral Presentation Paper - "3D Point Cloud Registration for Localization using a Deep Neural Network Auto-Encoder"

Authors: Gil Elbaz, Tamar Avraham, Prof. Anath Fischer

Technion - Israel Institute of Technology

*An RSCS implementation is included.In addition a fixed-RSCS algorithm is also implemented.It is an augmentation of the original algorithm that allows for better parametric control.Using this you can define exactly how many Super-points should be created, how many points in each Super-point.

*The basis code for the Super-point Auto-encoder Feature generator will be included.

*Requires Python 3.5 or higher

About

CVPR Paper - "3D Point Cloud Registration for Localization using a Deep Neural Network Auto-Encoder" - Partial Implementation Code

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages


[8]ページ先頭

©2009-2025 Movatter.jp