Browsing 41-Issue 7 by Subject "based models"
Now showing items 1-5 of 5
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MODNet: Multi-offset Point Cloud Denoising Network Customized for Multi-scale Patches
(The Eurographics Association and John Wiley & Sons Ltd., 2022)The intricacy of 3D surfaces often results cutting-edge point cloud denoising (PCD) models in surface degradation including remnant noise, wrongly-removed geometric details. Although using multi-scale patches to encode the ... -
SIGDT: 2D Curve Reconstruction
(The Eurographics Association and John Wiley & Sons Ltd., 2022)Determining connectivity between points and reconstructing their shape boundaries are long-standing problems in computer graphics. One possible approach to solve these problems is to use a proximity graph. We propose a new ... -
SO(3)-Pose: SO(3)-Equivariance Learning for 6D Object Pose Estimation
(The Eurographics Association and John Wiley & Sons Ltd., 2022)6D pose estimation of rigid objects from RGB-D images is crucial for object grasping and manipulation in robotics. Although RGB channels and the depth (D) channel are often complementary, providing respectively the appearance ... -
USTNet: Unsupervised Shape-to-Shape Translation via Disentangled Representations
(The Eurographics Association and John Wiley & Sons Ltd., 2022)We propose USTNet, a novel deep learning approach designed for learning shape-to-shape translation from unpaired domains in an unsupervised manner. The core of our approach lies in disentangled representation learning that ... -
UTOPIC: Uncertainty-aware Overlap Prediction Network for Partial Point Cloud Registration
(The Eurographics Association and John Wiley & Sons Ltd., 2022)High-confidence overlap prediction and accurate correspondences are critical for cutting-edge models to align paired point clouds in a partial-to-partial manner. However, there inherently exists uncertainty between the ...