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Recent advancements in learning algorithms for point clouds: An updated overview
Recent advancements in self-driving cars, robotics, and remote sensing have widened the
range of applications for 3D Point Cloud (PC) data. This data format poses several new …
range of applications for 3D Point Cloud (PC) data. This data format poses several new …
Delicate textured mesh recovery from nerf via adaptive surface refinement
Abstract Neural Radiance Fields (NeRF) have constituted a remarkable breakthrough in
image-based 3D reconstruction. However, their implicit volumetric representations differ …
image-based 3D reconstruction. However, their implicit volumetric representations differ …
Meshdiffusion: Score-based generative 3d mesh modeling
Z Liu, Y Feng, MJ Black, D Nowrouzezahrai… - arxiv preprint arxiv …, 2023 - arxiv.org
We consider the task of generating realistic 3D shapes, which is useful for a variety of
applications such as automatic scene generation and physical simulation. Compared to …
applications such as automatic scene generation and physical simulation. Compared to …
[HTML][HTML] In situ characterization of heterogeneous surface wetting in porous materials
The performance of nano-and micro-porous materials in capturing and releasing fluids, such
as during CO 2 geo-storage and water/gas removal in fuel cells and electrolyzers, is …
as during CO 2 geo-storage and water/gas removal in fuel cells and electrolyzers, is …
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 …
Ners: Neural reflectance surfaces for sparse-view 3d reconstruction in the wild
J Zhang, G Yang, S Tulsiani… - Advances in Neural …, 2021 - proceedings.neurips.cc
Recent history has seen a tremendous growth of work exploring implicit representations of
geometry and radiance, popularized through Neural Radiance Fields (NeRF). Such works …
geometry and radiance, popularized through Neural Radiance Fields (NeRF). Such works …
Large steps in inverse rendering of geometry
B Nicolet, A Jacobson, W Jakob - ACM Transactions on Graphics (TOG), 2021 - dl.acm.org
Inverse reconstruction from images is a central problem in many scientific and engineering
disciplines. Recent progress on differentiable rendering has led to methods that can …
disciplines. Recent progress on differentiable rendering has led to methods that can …
Urban radiance field representation with deformable neural mesh primitives
Abstract Neural Radiance Fields (NeRFs) have achieved great success in the past few
years. However, most current methods still require intensive resources due to ray marching …
years. However, most current methods still require intensive resources due to ray marching …
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 …
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 …