A Survey of Non‐Rigid 3D Registration
Non‐rigid registration computes an alignment between a source surface with a target
surface in a non‐rigid manner. In the past decade, with the advances in 3D sensing …
surface in a non‐rigid manner. In the past decade, with the advances in 3D sensing …
State of the art in surface reconstruction from point clouds
M Berger, A Tagliasacchi, LM Seversky… - … Conference of the …, 2014 - infoscience.epfl.ch
The area of surface reconstruction has seen substantial progress in the past two decades.
The traditional problem addressed by surface reconstruction is to recover the digital …
The traditional problem addressed by surface reconstruction is to recover the digital …
Local implicit grid representations for 3d scenes
Shape priors learned from data are commonly used to reconstruct 3D objects from partial or
noisy data. Yet no such shape priors are available for indoor scenes, since typical 3D …
noisy data. Yet no such shape priors are available for indoor scenes, since typical 3D …
Pcn: Point completion network
Shape completion, the problem of estimating the complete geometry of objects from partial
observations, lies at the core of many vision and robotics applications. In this work, we …
observations, lies at the core of many vision and robotics applications. In this work, we …
Morphing and sampling network for dense point cloud completion
Abstract 3D point cloud completion, the task of inferring the complete geometric shape from
a partial point cloud, has been attracting attention in the community. For acquiring high …
a partial point cloud, has been attracting attention in the community. For acquiring high …
Shape completion using 3d-encoder-predictor cnns and shape synthesis
A Dai, C Ruizhongtai Qi… - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
We introduce a data-driven approach to complete partial 3D shapes through a combination
of volumetric deep neural networks and 3D shape synthesis. From a partially-scanned input …
of volumetric deep neural networks and 3D shape synthesis. From a partially-scanned input …
Neural scene flow prior
X Li, J Kaesemodel Pontes… - Advances in Neural …, 2021 - proceedings.neurips.cc
Before the deep learning revolution, many perception algorithms were based on runtime
optimization in conjunction with a strong prior/regularization penalty. A prime example of this …
optimization in conjunction with a strong prior/regularization penalty. A prime example of this …
A survey of surface reconstruction from point clouds
M Berger, A Tagliasacchi, LM Seversky… - Computer graphics …, 2017 - Wiley Online Library
The area of surface reconstruction has seen substantial progress in the past two decades.
The traditional problem addressed by surface reconstruction is to recover the digital …
The traditional problem addressed by surface reconstruction is to recover the digital …
Scancomplete: Large-scale scene completion and semantic segmentation for 3d scans
We introduce ScanComplete, a novel data-driven approach for taking an incomplete 3D
scan of a scene as input and predicting a complete 3D model along with per-voxel semantic …
scan of a scene as input and predicting a complete 3D model along with per-voxel semantic …
Neural dual contouring
We introduce neural dual contouring (NDC), a new data-driven approach to mesh
reconstruction based on dual contouring (DC). Like traditional DC, it produces exactly one …
reconstruction based on dual contouring (DC). Like traditional DC, it produces exactly one …