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DiffPMAE: Diffusion Masked Autoencoders for Point Cloud Reconstruction

DiffPMAE: Diffusion Masked Autoencoders for Point Cloud Reconstruction

Yanlong Li
Chamara Madarasingha
Kanchana Thilakarathna
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Papers citing "DiffPMAE: Diffusion Masked Autoencoders for Point Cloud Reconstruction"

6 / 6 papers shown
Title
Particle Trajectory Representation Learning with Masked Point Modeling
Particle Trajectory Representation Learning with Masked Point Modeling
Sam Young
Yeon-jae Jwa
Kazuhiro Terao
3DPC
69
1
0
04 Feb 2025
PU-EdgeFormer: Edge Transformer for Dense Prediction in Point Cloud Upsampling
PU-EdgeFormer: Edge Transformer for Dense Prediction in Point Cloud Upsampling
Dohoon Kim
Minwoo Shin
J. Paik
3DPC
ViT
27
2
0
02 May 2023
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
178
244
0
28 May 2022
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
305
7,443
0
11 Nov 2021
Diffusion Probabilistic Models for 3D Point Cloud Generation
Diffusion Probabilistic Models for 3D Point Cloud Generation
Shitong Luo
Wei Hu
3DPC
180
721
0
02 Mar 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
126
268
0
07 Jan 2021