37 citations · 84 across the 13 of their papers we have counts for
4 papers · 1 filter
Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud Learning
Yabin Zhang, Jiehong Lin, Ruihuang Li +2
Masked autoencoder has demonstrated its effectiveness in self-supervised point cloud learning. Considering that masking is a kind of corruption, in this work we explore a more gene…
DCL-Net: Deep Correspondence Learning Network for 6D Pose Estimation
Hongyang Li, Jiehong Lin, Kui Jia
Establishment of point correspondence between camera and object coordinate systems is a promising way to solve 6D object poses. However, surrogate objectives of correspondence lear…
Category-Level 6D Object Pose and Size Estimation using Self-Supervised Deep Prior Deformation Networks
Jiehong Lin, Zewei Wei, Changxing Ding +1
It is difficult to precisely annotate object instances and their semantics in 3D space, and as such, synthetic data are extensively used for these tasks, e.g., category-level 6D ob…
Masked Surfel Prediction for Self-Supervised Point Cloud Learning
Yabin Zhang, Jiehong Lin, Chenhang He +3
Masked auto-encoding is a popular and effective self-supervised learning approach to point cloud learning. However, most of the existing methods reconstruct only the masked points…