4 papers
6D Pose Estimation on Point Cloud Data through Prior Knowledge Integration: A Case Study in Autonomous Disassembly
Chengzhi Wu, Hao Fu, Jan-Philipp Kaiser +5
The accurate estimation of 6D pose remains a challenging task within the computer vision domain, even when utilizing 3D point cloud data. Conversely, in the manufacturing domain, i…
A Cross Branch Fusion-Based Contrastive Learning Framework for Point Cloud Self-supervised Learning
Chengzhi Wu, Qianliang Huang, Kun Jin +2
Contrastive learning is an essential method in self-supervised learning. It primarily employs a multi-branch strategy to compare latent representations obtained from different bran…
SAMBLE: Shape-Specific Point Cloud Sampling for an Optimal Trade-Off Between Local Detail and Global Uniformity
Chengzhi Wu, Yuxin Wan, Hao Fu +5
Driven by the increasing demand for accurate and efficient representation of 3D data in various domains, point cloud sampling has emerged as a pivotal research topic in 3D computer…
Partially Observable Gaussian Process Network and Doubly Stochastic Variational Inference
Saksham Kiroriwal, Julius Pfrommer, Jürgen Beyerer
To reduce the curse of dimensionality for Gaussian processes (GP), they can be decomposed into a Gaussian Process Network (GPN) of coupled subprocesses with lower dimensionality. I…