Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales

Terms and Conditions

Twitter GitHub LinkedIn Bluesky Youtube

© 2026 ResearchTrend.AI, All rights reserved.

Home
Papers
2308.06271
Cited By

Rotation-Invariant Random Features Provide a Strong Baseline for Machine
Learning on 3D Point Clouds

Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds

27 July 2023

Rebecca Willett

ArXiv (abs)PDF HTML

Papers citing "Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds"

2 / 2 papers shown

TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR
Object Detection with Unsupervised Pre-Training

TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-TrainingBritish Machine Vision Conference (BMVC), 2024

Hubert P. H. Shum

274

2

0

25 Aug 2024

RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D
LiDAR Segmentation

RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation

Hubert P. H. Shum

337

16

0

14 Jul 2024