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Multi-View Representation is What You Need for Point-Cloud Pre-Training

Multi-View Representation is What You Need for Point-Cloud Pre-Training

5 June 2023
Siming Yan
Chen Song
Youkang Kong
Qi-Xing Huang
    3DPC
ArXivPDFHTML

Papers citing "Multi-View Representation is What You Need for Point-Cloud Pre-Training"

12 / 12 papers shown
Title
P3P: Pseudo-3D Pre-training for Scaling 3D Masked Autoencoders
P3P: Pseudo-3D Pre-training for Scaling 3D Masked Autoencoders
Xuechao Chen
Ying Chen
Jialin Li
Qiang Nie
Hanqiu Deng
Qixing Huang
Yang Li
Yang Li
3DPC
58
0
0
19 Aug 2024
3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud
  Pretraining
3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining
Siming Yan
Yu-Qi Yang
Yu-Xiao Guo
Hao Pan
Peng-shuai Wang
Xin Tong
Yang Liu
Qi-Xing Huang
3DPC
22
15
0
14 Apr 2023
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds
Haiyang Wang
Lihe Ding
Shaocong Dong
Shaoshuai Shi
Aoxue Li
Jianan Li
Zhenguo Li
Liwei Wang
3DPC
135
67
0
09 Oct 2022
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud
  Pre-training
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
Renrui Zhang
Ziyu Guo
Rongyao Fang
Bingyan Zhao
Dong Wang
Yu Qiao
Hongsheng Li
Peng Gao
3DPC
167
241
0
28 May 2022
Pretraining is All You Need for Image-to-Image Translation
Pretraining is All You Need for Image-to-Image Translation
Tengfei Wang
Ting Zhang
Bo Zhang
Hao Ouyang
Dong Chen
Qifeng Chen
Fang Wen
DiffM
176
177
0
25 May 2022
4DContrast: Contrastive Learning with Dynamic Correspondences for 3D
  Scene Understanding
4DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understanding
Yujin Chen
Matthias Nießner
Angela Dai
3DPC
103
57
0
06 Dec 2021
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
258
7,337
0
11 Nov 2021
Self-Supervised Pretraining of 3D Features on any Point-Cloud
Self-Supervised Pretraining of 3D Features on any Point-Cloud
Zaiwei Zhang
Rohit Girdhar
Armand Joulin
Ishan Misra
3DPC
120
267
0
07 Jan 2021
PointContrast: Unsupervised Pre-training for 3D Point Cloud
  Understanding
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding
Saining Xie
Jiatao Gu
Demi Guo
C. Qi
Leonidas J. Guibas
Or Litany
3DPC
136
618
0
21 Jul 2020
Joint 2D-3D-Semantic Data for Indoor Scene Understanding
Joint 2D-3D-Semantic Data for Indoor Scene Understanding
Iro Armeni
S. Sax
Amir Zamir
Silvio Savarese
3DV
3DPC
113
864
0
03 Feb 2017
PointNet: Deep Learning on Point Sets for 3D Classification and
  Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas J. Guibas
3DH
3DPC
3DV
PINN
213
13,886
0
02 Dec 2016
Indoor Semantic Segmentation using depth information
Indoor Semantic Segmentation using depth information
Camille Couprie
C. Farabet
Laurent Najman
Yann LeCun
SSeg
MDE
62
473
0
16 Jan 2013
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