Towards compact 3d representations via point feature enhancement masked autoencoders
Learning 3D representation plays a critical role in masked autoencoder (MAE) based pre-
training methods for point cloud, including single-modal and cross-modal based MAE …
training methods for point cloud, including single-modal and cross-modal based MAE …
Pcp-mae: Learning to predict centers for point masked autoencoders
Masked autoencoder has been widely explored in point cloud self-supervised learning,
whereby the point cloud is generally divided into visible and masked parts. These methods …
whereby the point cloud is generally divided into visible and masked parts. These methods …
Pre-training Point Cloud Compact Model with Partial-aware Reconstruction
The pre-trained point cloud model based on Masked Point Modeling (MPM) has exhibited
substantial improvements across various tasks. However, two drawbacks hinder their …
substantial improvements across various tasks. However, two drawbacks hinder their …
LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling
The pre-trained point cloud model based on Masked Point Modeling (MPM) has exhibited
substantial improvements across various tasks. However, these models heavily rely on the …
substantial improvements across various tasks. However, these models heavily rely on the …
LR-MAE: Locate while Reconstructing with Masked Autoencoders for Point Cloud Self-supervised Learning
H Ji, Y Zha, Q Liao - 2024 IEEE International Conference on …, 2024 - ieeexplore.ieee.org
As an efficient self-supervised pre-training approach, Masked autoencoder (MAE) has
shown promising improvement across various 3D point cloud understanding tasks …
shown promising improvement across various 3D point cloud understanding tasks …