ResearchTrend.AI
SieveNet: Selecting Point-Based Features for Mesh Networks

SieveNet: Selecting Point-Based Features for Mesh Networks

Shengchao Yuan
Yishun Dou
Rui Shi
Bingbing Ni
Zhong Zheng
    3DPC
ArXivPDFHTML

Papers citing "SieveNet: Selecting Point-Based Features for Mesh Networks"

5 / 5 papers shown
Title
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds
Mutian Xu
Runyu Ding
Hengshuang Zhao
Xiaojuan Qi
3DPC
94
394
0
26 Mar 2021
Point Transformer
Point Transformer
Nico Engel
Vasileios Belagiannis
Klaus C. J. Dietmayer
3DPC
140
1,966
0
02 Nov 2020
Continuous Geodesic Convolutions for Learning on 3D Shapes
Continuous Geodesic Convolutions for Learning on 3D Shapes
Zhangsihao Yang
Or Litany
Tolga Birdal
Srinath Sridhar
Leonidas Guibas
3DH
3DPC
3DV
37
30
0
06 Feb 2020
KPConv: Flexible and Deformable Convolution for Point Clouds
KPConv: Flexible and Deformable Convolution for Point Clouds
Hugues Thomas
C. Qi
Jean-Emmanuel Deschaud
B. Marcotegui
F. Goulette
Leonidas Guibas
3DPC
124
2,518
0
18 Apr 2019
MeshNet: Mesh Neural Network for 3D Shape Representation
MeshNet: Mesh Neural Network for 3D Shape Representation
Yutong Feng
Yifan Feng
Haoxuan You
Xibin Zhao
Yue Gao
3DV
3DH
42
303
0
28 Nov 2018