ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1912.05905
  4. Cited By
LatticeNet: Fast Point Cloud Segmentation Using Permutohedral Lattices

LatticeNet: Fast Point Cloud Segmentation Using Permutohedral Lattices

12 December 2019
R. Rosu
Peer Schütt
Jan Quenzel
Sven Behnke
    3DPC
    3DV
ArXivPDFHTML

Papers citing "LatticeNet: Fast Point Cloud Segmentation Using Permutohedral Lattices"

16 / 16 papers shown
Title
Deep Learning on 3D Semantic Segmentation: A Detailed Review
Deep Learning on 3D Semantic Segmentation: A Detailed Review
Thodoris Betsas
Andreas Georgopoulos
Anastasios Doulamis
Pierre Grussenmeyer
3DV
3DPC
33
1
0
04 Nov 2024
A Review of Panoptic Segmentation for Mobile Mapping Point Clouds
A Review of Panoptic Segmentation for Mobile Mapping Point Clouds
Binbin Xiang
Yuanwen Yue
T. Peters
Konrad Schindler
3DPC
22
7
0
27 Apr 2023
Semantic Segmentation of Urban Textured Meshes Through Point Sampling
Semantic Segmentation of Urban Textured Meshes Through Point Sampling
Grégoire Grzeczkowicz
Bruno Vallet
3DPC
17
5
0
21 Feb 2023
Scalable SoftGroup for 3D Instance Segmentation on Point Clouds
Scalable SoftGroup for 3D Instance Segmentation on Point Clouds
Thang Vu
Kookhoi Kim
Tung M. Luu
Xuan Thanh Nguyen
Junyeong Kim
Chang D. Yoo
3DPC
27
22
0
17 Sep 2022
A Near Sensor Edge Computing System for Point Cloud Semantic
  Segmentation
A Near Sensor Edge Computing System for Point Cloud Semantic Segmentation
Lin Bai
Yiming Zhao
Xinming Huang
3DPC
13
3
0
12 Jul 2022
Contrastive Boundary Learning for Point Cloud Segmentation
Contrastive Boundary Learning for Point Cloud Segmentation
Liyao Tang
Yibing Zhan
Zhe Chen
Baosheng Yu
Dacheng Tao
3DPC
22
102
0
10 Mar 2022
SensatUrban: Learning Semantics from Urban-Scale Photogrammetric Point
  Clouds
SensatUrban: Learning Semantics from Urban-Scale Photogrammetric Point Clouds
Qingyong Hu
Bo Yang
Sheikh Khalid
W. Xiao
Niki Trigoni
Andrew Markham
3DPC
26
85
0
12 Jan 2022
Fast Point Transformer
Fast Point Transformer
Chunghyun Park
Yoonwoo Jeong
Minsu Cho
Jaesik Park
3DPC
ViT
30
168
0
09 Dec 2021
ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via
  Regularized Domain Concatenation
ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenation
Lingdong Kong
N. Quader
Venice Erin Liong
21
48
0
30 Nov 2021
Efficient Urban-scale Point Clouds Segmentation with BEV Projection
Efficient Urban-scale Point Clouds Segmentation with BEV Projection
Zhenhong Zou
Yizhe Li
3DPC
34
8
0
19 Sep 2021
LiDAR-based Recurrent 3D Semantic Segmentation with Temporal Memory
  Alignment
LiDAR-based Recurrent 3D Semantic Segmentation with Temporal Memory Alignment
Fabian Duerr
Mario Pfaller
H. Weigel
Jürgen Beyerer
3DPC
15
33
0
03 Mar 2021
(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection
  for Sparse Semantic Segmentation Network
(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network
Ran Cheng
Ryan Razani
E. Taghavi
Enxu Li
Bingbing Liu
3DPC
158
241
0
08 Feb 2021
TORNADO-Net: mulTiview tOtal vaRiatioN semAntic segmentation with
  Diamond inceptiOn module
TORNADO-Net: mulTiview tOtal vaRiatioN semAntic segmentation with Diamond inceptiOn module
Martin Gerdzhev
Ryan Razani
E. Taghavi
Bingbing Liu
3DPC
110
70
0
24 Aug 2020
Cascaded Non-local Neural Network for Point Cloud Semantic Segmentation
Cascaded Non-local Neural Network for Point Cloud Semantic Segmentation
Mingmei Cheng
Le Hui
Jin Xie
Jian Yang
Hui Kong
3DPC
18
21
0
30 Jul 2020
Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey and
  Experimental Study
Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey and Experimental Study
Biao Gao
Yancheng Pan
Chengkun Li
Sibo Geng
Huijing Zhao
3DPC
19
25
0
08 Jun 2020
Geometric deep learning on graphs and manifolds using mixture model CNNs
Geometric deep learning on graphs and manifolds using mixture model CNNs
Federico Monti
Davide Boscaini
Jonathan Masci
Emanuele Rodolà
Jan Svoboda
M. Bronstein
GNN
251
1,811
0
25 Nov 2016
1