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Back to amosgropp/igr

Open-source alternatives to Amosgropp IGR

30 open-source projects similar to amosgropp/igr, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Amosgropp IGR alternative.

  • matanatz/salmatanatz avatar

    matanatz/SAL

    90View on GitHub↗

    SAL: Sign Agnostic Learning of Shapes From Raw Data

    Python
    View on GitHub↗90
  • lululxvi/deepxdelululxvi avatar

    lululxvi/deepxde

    3,874View on GitHub↗

    DeepXDE is a scientific machine learning library and deep learning PDE solver used to compute solutions for forward and inverse ordinary, partial, and integro-differential equations. It functions as a physics-informed neural network library that embeds physical laws and boundary conditions directly into the neural network loss function. The project provides a deep operator network framework for learning operator mappings that approximate relationships between functions in multiphysics problems. It is implemented as a multi-backend tensor library, allowing the system to switch between differen

    Pythondeep-learningdeeponetjax
    View on GitHub↗3,874
  • google/dracogoogle avatar

    google/draco

    7,357View on GitHub↗

    Draco is a library and toolset for compressing, transcoding, and decoding 3D geometric meshes and point cloud data. Its primary purpose is to reduce storage size and transmission bandwidth for 3D assets. The project includes a geometry optimizer specifically for glTF file containers to reduce asset footprints. It also features a hardened decoder designed to process malformed or untrusted 3D geometric data safely to prevent memory corruption and crashes. The software covers a broad range of 3D data processing capabilities, including geometric data reconstruction, point attribute management, a

    C++
    View on GitHub↗7,357
  • nv-tlabs/get3dnv-tlabs avatar

    nv-tlabs/GET3D

    4,441View 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↗4,441

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  • openai/point-eopenai avatar

    openai/point-e

    6,886View 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↗6,886
  • fwilliams/neural-splinesfwilliams avatar

    fwilliams/neural-splines

    98View on GitHub↗

    This repository contains the official implementation of the CVPR 2021 (Oral) paper Neural Splines: Fitting 3D Surfaces with Infinitely-Wide Neural Networks.

    Python
    View on GitHub↗98
  • gdaosu/vis2meshGDAOSU avatar

    GDAOSU/vis2mesh

    106View on GitHub↗

    This is the offical repository of the paper:

    C++
    View on GitHub↗106
  • isl-org/adaptive-surface-reconstructionisl-org avatar

    isl-org/adaptive-surface-reconstruction

    63View on GitHub↗

    This repository contains code for the ICCV 2021 paper

    Python
    View on GitHub↗63
  • jchibane/ndfjchibane avatar

    jchibane/ndf

    206View on GitHub↗

    Paper - Supplementaty - Project Website - Arxiv - Published in NeurIPS 2020.

    Python
    View on GitHub↗206
  • 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
  • mabaorui/noise2noisemappingmabaorui avatar

    mabaorui/Noise2NoiseMapping

    128View on GitHub↗

    Project Page | Personal Web Page | Paper

    Python
    View on GitHub↗128
  • mabaorui/onsurfacepriormabaorui avatar

    mabaorui/OnSurfacePrior

    191View on GitHub↗

    Personal Web Pages | Paper | Project Page

    Python
    View on GitHub↗191
  • mabaorui/predictablecontextpriormabaorui avatar

    mabaorui/predictablecontextprior

    172View on GitHub↗

    Personal Web Pages | Paper | Project Page This repository contains the code to reproduce the results from the paper. Surface Reconstruction from Point Clouds by Learning Predictive Context Priors.

    Python
    View on GitHub↗172
  • matanatz/saldmatanatz avatar

    matanatz/SALD

    14View on GitHub↗

    This repository contains an implementation to the ICLR 2021 paper SALD: Sign Agnostic Learning with Derivatives.

    Python
    View on GitHub↗14
  • microsoft/dualoctreegnnmicrosoft avatar

    microsoft/DualOctreeGNN

    149View on GitHub↗

    This repository contains the implementation of our papers Dual Octree Graph Networks. The experiments are conducted on Ubuntu 18.04 with 4 V400 GPUs (32GB memory). The code is released under the MIT license.

    Python
    View on GitHub↗149
  • mohamed-ebbed/scan2meshmohamed-ebbed avatar

    mohamed-ebbed/Scan2Mesh

    4View on GitHub↗

    A non-official PyTorch implementation for Scan2Mesh: From Unstructured Range Scans to 3D Meshes paper on ShapeNet dataset

    Python
    View on GitHub↗4
  • mrakotosaon/diff-surface-triangulationmrakotosaon avatar

    mrakotosaon/diff-surface-triangulation

    109View on GitHub↗

    This is our implementation of the paper Differentiable Surface Triangulation that enables optimization for any per-vertex or per-face differentiable objective function over the space of underlying surface triangulations.

    C++
    View on GitHub↗109
  • mrakotosaon/dse-meshingmrakotosaon avatar

    mrakotosaon/dse-meshing

    55View on GitHub↗

    This is our implementation of the paper "Learning Delaunay Surface Elements for Mesh Reconstruction" at CVPR 2021 (oral), a method for mesh recontruction from a point cloud.

    C++
    View on GitHub↗55
  • nmwsharp/learned-triangulationnmwsharp avatar

    nmwsharp/learned-triangulation

    116View on GitHub↗

    Source code & pretrained model for "PointTriNet: Learned Triangulation of 3D Point Sets", by Nicholas Sharp and Maks Ovsjanikov at ECCV 2020.

    Python
    View on GitHub↗116
  • nvlabs/meshletsNVlabs avatar

    NVlabs/meshlets

    49View on GitHub↗

    Meshlet Priors for 3D Mesh Reconstruction Abhishek Badki, Orazio Gallo, Jan Kautz, Pradeep Sen IEEE CVPR 2020

    View on GitHub↗49
  • wi-sc/nvfWi-sc avatar

    Wi-sc/NVF

    38View on GitHub↗

    Official implementation of Neural Vector Fields (NVF). Feel free to use this code for academic work, but please cite the following: `` @misc{yang2023neural, title={Neural Vector Fields: Implicit Representation by Explicit Learning}, author={Xianghui Yang and Guosheng Lin and Zhenghao Chen and…

    Python
    View on GitHub↗38
  • chenchao15/neuraltpschenchao15 avatar

    chenchao15/NeuralTPS

    49View on GitHub↗

    If you find this project useful in your research, please consider citing:

    Python
    View on GitHub↗49
  • 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
  • erlerphilipp/points2surfErlerPhilipp avatar

    ErlerPhilipp/points2surf

    510View on GitHub↗

    Please see our follow-up work PPSurf. It's easier to use, much faster and better.

    Python
    View on GitHub↗510
  • fwilliams/deep-geometric-priorfwilliams avatar

    fwilliams/deep-geometric-prior

    143View on GitHub↗

    The reference implementaiton for the CVPR 2019 paper Deep Geometric Prior for Surface Reconstruction.

    Python
    View on GitHub↗143
  • andy97/deepmlsAndy97 avatar

    Andy97/DeepMLS

    137View on GitHub↗

    This repository contains the implementation of the paper:

    Python
    View on GitHub↗137
  • raphaelsulzer/dgnnraphaelsulzer avatar

    raphaelsulzer/dgnn

    45View on GitHub↗

    MVS point cloud Ours ConvONet 1

    Python
    View on GitHub↗45
  • rsy6318/geoudfrsy6318 avatar

    rsy6318/GeoUDF

    131View on GitHub↗

    ` pytorch #1.10.0+cu111 pytorch3d #0.6.2 open3d trimesh point-cloud-utils cd pointnet2opslib python setup.py install Download the data from Google Drive (These shapes are processed by DISN, remove the interior and non-manifold structures.) Then use the codes in scripts to get the dataset.…

    Python
    View on GitHub↗131
  • simongiebenhain/air-netsSimonGiebenhain avatar

    SimonGiebenhain/AIR-Nets

    34View on GitHub↗

    Preprint | Supplementary | Accepted at the International Conference on 3D Vision (3DV)

    Python
    View on GitHub↗34
  • tangjiapeng/sa-convonettangjiapeng avatar

    tangjiapeng/SA-ConvONet

    96View on GitHub↗

    Paper | Supplementary | Slides | Video | Project Page

    Python
    View on GitHub↗96