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08/29/2023
WrappingNet: Mesh Autoencoder via Deep Sphere Deformation
There have been recent efforts to learn more meaningful representations ...
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06/19/2023
Concavity-Induced Distance for Unoriented Point Cloud Decomposition
We propose Concavity-induced Distance (CID) as a novel way to measure th...
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09/09/2022
GRASP-Net: Geometric Residual Analysis and Synthesis for Point Cloud Compression
Point cloud compression (PCC) is a key enabler for various 3-D applicati...
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04/01/2021
FESTA: Flow Estimation via Spatial-Temporal Attention for Scene Point Clouds
Scene flow depicts the dynamics of a 3D scene, which is critical for var...
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06/17/2020
TearingNet: Point Cloud Autoencoder to Learn Topology-Friendly Representations
Topology matters. Despite the recent success of point cloud processing w...
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02/11/2020
3D Point Cloud Enhancement using Graph-Modelled Multiview Depth Measurements
A 3D point cloud is often synthesized from depth measurements collected ...
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05/11/2019
Deep Unsupervised Learning of 3D Point Clouds via Graph Topology Inference and Filtering
We propose a deep autoencoder with graph topology inference and filterin...
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12/19/2017
FoldingNet: Interpretable Unsupervised Learning on 3D Point Clouds
Recent deep networks that directly handle points in a point set, e.g., P...
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12/19/2017
Neighbors Do Help: Deeply Exploiting Local Structures of Point Clouds
Unlike on images, semantic learning on 3D point clouds using a deep netw...
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02/02/2017
Guided Signal Reconstruction Theory
An axiomatic approach to signal reconstruction is formulated, involving ...
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09/04/2015
