research
∙
03/29/2022
3D Shape Reconstruction from 2D Images with Disentangled Attribute Flow
Reconstructing 3D shape from a single 2D image is a challenging task, wh...
share
research
∙
03/26/2022
Self-Supervised Point Cloud Representation Learning with Occlusion Auto-Encoder
Learning representations for point clouds is an important task in 3D com...
research
∙
03/26/2022
Learning Deep Implicit Functions for 3D Shapes with Dynamic Code Clouds
Deep Implicit Function (DIF) has gained popularity as an efficient 3D sh...
research
∙
02/19/2022
PMP-Net++: Point Cloud Completion by Transformer-Enhanced Multi-step Point Moving Paths
Point cloud completion concerns to predict missing part for incomplete 3...
research
∙
02/18/2022
Snowflake Point Deconvolution for Point Cloud Completion and Generation with Skip-Transformer
Most existing point cloud completion methods suffered from discrete natu...
research
∙
12/22/2021
Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and Results
As real-scanned point clouds are mostly partial due to occlusions and vi...
research
∙
11/23/2021
MFM-Net: Unpaired Shape Completion Network with Multi-stage Feature Matching
Unpaired 3D object completion aims to predict a complete 3D shape from a...
research
∙
08/10/2021
SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer
Point cloud completion aims to predict a complete shape in high accuracy...
research
∙
03/14/2021
Cycle4Completion: Unpaired Point Cloud Completion using Cycle Transformation with Missing Region Coding
In this paper, we present a novel unpaired point cloud completion networ...
research
∙
12/07/2020
PMP-Net: Point Cloud Completion by Learning Multi-step Point Moving Paths
The task of point cloud completion aims to predict the missing part for ...
research
∙
05/08/2020
Point Cloud Completion by Skip-attention Network with Hierarchical Folding
Point cloud completion aims to infer the complete geometries for missing...
research
∙
08/29/2019
Point2SpatialCapsule: Aggregating Features and Spatial Relationships of Local Regions on Point Clouds using Spatial-aware Capsules
Learning discriminative shape representation directly on point clouds is...
research
∙
08/02/2019
L2G Auto-encoder: Understanding Point Clouds by Local-to-Global Reconstruction with Hierarchical Self-Attention
Auto-encoder is an important architecture to understand point clouds in ...
research
∙
04/17/2019
Adversarial Cross-Modal Retrieval via Learning and Transferring Single-Modal Similarities
Cross-modal retrieval aims to retrieve relevant data across different mo...
research
∙
11/05/2018
