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Totoro97 avatar

Totoro97/NeuS

0
View on GitHub↗
1,774 stars·225 forks·Python·MIT·10 views

NeuS

Code release for NeuS

Features

  • Surface Reconstruction - Learns implicit surfaces via volume rendering.

Star history

Star history chart for totoro97/neusStar history chart for totoro97/neus

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Frequently asked questions

What does totoro97/neus do?

Code release for NeuS

What are the main features of totoro97/neus?

The main features of totoro97/neus are: Surface Reconstruction.

Which projects share features with totoro97/neus?

Projects with overlapping indexed features include: xxlong0/wonder3d — Wonder3D is a diffusion-based system for single image 3D reconstruction. It generates high-detail 3D meshes from a… ventusff/neurecon — Multi-view 3D reconstruction using neural rendering. Unofficial implementation of UNISURF, VolSDF, NeuS and more. xmeng525/neat — This is the official repo for the implementation of NeAT: Learning Neural Implicit Surfaces with Arbitrary Topologies…

Projects sharing features with NeuS

These projects share indexed features with NeuS. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • xxlong0/wonder3dxxlong0 avatar

    xxlong0/Wonder3D

    5,388View on GitHub↗

    Wonder3D is a diffusion-based system for single image 3D reconstruction. It generates high-detail 3D meshes from a single input image by producing consistent multi-view normal maps and color images. The pipeline functions as a multi-view normal map generator and a textured mesh extractor. It uses cross-domain multi-view synthesis to create view-dependent maps, which are then converted into 3D geometry through radiance fusion and memory-efficient surface reconstruction. The project covers 3D mesh generation, multi-view generation, and textured 3D modeling. It also includes capabilities for tr

    Python3d-aigc3d-generation3dgeneration
    View on GitHub↗5,388
  • ventusff/neureconventusff avatar

    ventusff/neurecon

    861View on GitHub↗

    Multi-view 3D reconstruction using neural rendering. Unofficial implementation of UNISURF, VolSDF, NeuS and more.

    Python
    View on GitHub↗861
  • xmeng525/neatxmeng525 avatar

    xmeng525/NeAT

    165View on GitHub↗

    This is the official repo for the implementation of NeAT: Learning Neural Implicit Surfaces with Arbitrary Topologies from Multi-view Images.

    Python
    View on GitHub↗165