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Andy97 avatar

Andy97/DeepMLS

0
View on GitHub↗

DeepMLS

This repository contains the implementation of the paper:

Features

  • Generative 3D Modeling - Implements deep implicit moving least-squares for reconstruction.

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  • Point Cloud Reconstruction - Deep implicit moving least-squares for 3D reconstruction.
  • 137 stars·23 forks·Python·MIT·13 views

    Star history

    Star history chart for andy97/deepmlsStar history chart for andy97/deepmls

    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.

    Projects sharing features with DeepMLS

    These projects share indexed features with DeepMLS. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
    • nv-tlabs/get3dnv-tlabs avatar

      nv-tlabs/GET3D

      4,424View on GitHub↗

      GET3D is a generative 3D mesh model and rendering framework designed to synthesize high-quality textured shapes and tetrahedral meshes. It functions as an image-to-3D reconstructor and text-to-3D generator, utilizing a differentiable 3D renderer to produce realistic visual perspectives and material effects. The system enables the creation of 3D assets from single 2D images, point clouds, or descriptive text prompts. It features a latent space interpolator for creating smooth transitions between different 3D objects and supports the independent control of geometry and texture. The project cov

      Python
      View on GitHub↗4,424
    • openai/point-eopenai avatar

      openai/point-e

      6,902View on GitHub↗

      Point-e is a system for 3D model synthesis that generates three-dimensional point clouds from natural language descriptions and two-dimensional images. It utilizes diffusion models to synthesize these spatial representations based on text prompts or source images. The project includes specialized tools for refining these outputs, such as a point cloud upsampler to increase the density and resolution of low-resolution models. It also provides a mesh converter that uses distance function regression to transform raw point cloud data into structured 3D meshes. The broader capability surface cove

      Python
      View on GitHub↗6,902
    • mabaorui/neuralpullmabaorui avatar

      mabaorui/NeuralPull

      181View on GitHub↗

      This repository contains the code to reproduce the results from the paper.

      Python
      View on GitHub↗181
    • colin97/point2meshColin97 avatar

      Colin97/Point2Mesh

      98View on GitHub↗

      Codes for Meshing Point Clouds with Predicted Intrinsic-Extrinsic Ratio Guidance (ECCV2020). paper

      C++
      View on GitHub↗98
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    Frequently asked questions

    What does andy97/deepmls do?

    This repository contains the implementation of the paper:

    What are the main features of andy97/deepmls?

    The main features of andy97/deepmls are: Generative 3D Modeling, Point Cloud Reconstruction.

    Which projects share features with andy97/deepmls?

    Projects with overlapping indexed features include: nv-tlabs/get3d — GET3D is a generative 3D mesh model and rendering framework designed to synthesize high-quality textured shapes and… openai/point-e — Point-e is a system for 3D model synthesis that generates three-dimensional point clouds from natural language… valeoai/poco — by: Alexandre Boulch and Renaud Marlet. colin97/point2mesh — Codes for Meshing Point Clouds with Predicted Intrinsic-Extrinsic Ratio Guidance (ECCV2020). [paper]. mabaorui/neuralpull — This repository contains the code to reproduce the results from the paper. openai/shap-e — Shap-E is a generative 3D modeling system that creates three-dimensional digital assets from natural language…