Surface Reconstruction

256 papers with code • 3 benchmarks • 9 datasets

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Libraries

Use these libraries to find Surface Reconstruction models and implementations
2 papers
860

Most implemented papers

NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

Totoro97/NeuS NeurIPS 2021

In NeuS, we propose to represent a surface as the zero-level set of a signed distance function (SDF) and develop a new volume rendering method to train a neural SDF representation.

Patch-based Progressive 3D Point Set Upsampling

yifita/3PU_pytorch CVPR 2019

We present a detail-driven deep neural network for point set upsampling.

Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance

lioryariv/idr NeurIPS 2020

In this work we address the challenging problem of multiview 3D surface reconstruction.

NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video

zju3dv/NeuralRecon CVPR 2021

We present a novel framework named NeuralRecon for real-time 3D scene reconstruction from a monocular video.

Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI

facebookresearch/habitat-matterport3d-dataset 16 Sep 2021

When compared to existing photorealistic 3D datasets such as Replica, MP3D, Gibson, and ScanNet, images rendered from HM3D have 20 - 85% higher visual fidelity w. r. t.

NeuS2: Fast Learning of Neural Implicit Surfaces for Multi-view Reconstruction

19reborn/NeuS2 ICCV 2023

Recent methods for neural surface representation and rendering, for example NeuS, have demonstrated the remarkably high-quality reconstruction of static scenes.

Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation

maxjiang93/DDSL ICLR 2019

It has been challenging to analyze signals with mixed topologies (for example, point cloud with surface mesh).

Controlling Neural Level Sets

matanatz/SAL NeurIPS 2019

In turn, the sample network can be used to incorporate the level set samples into a loss function of interest.

HumanMeshNet: Polygonal Mesh Recovery of Humans

yudhik11/HumanMeshNet 19 Aug 2019

3D Human Body Reconstruction from a monocular image is an important problem in computer vision with applications in virtual and augmented reality platforms, animation industry, en-commerce domain, etc.

Surface Reconstruction from 3D Line Segments

palanglois/line-surface-reconstruction 1 Nov 2019

In man-made environments such as indoor scenes, when point-based 3D reconstruction fails due to the lack of texture, lines can still be detected and used to support surfaces.