Open-source alternatives to NeuralPull

Shap-E is a generative 3D modeling system that creates three-dimensional digital assets from natural language descriptions or two-dimensional images. It functions as a generative model capable of producing three-dimensional implicit functions and assets. The project includes a 3D latent encoder that converts trimeshes and 3D models into latent representations using point clouds and multiview renders. It utilizes an image-to-3D generator to produce assets from synthetic view images and a text-to-3D generator to build shapes from text prompts. The system implements a pipeline involving latent

Threestudio is a 3D generative AI framework designed to create three-dimensional assets from text prompts and images. It provides specialized pipelines for text-to-3D generation and image-to-3D reconstruction, utilizing a neural radiance field trainer to produce geometry and textures. The framework is distinguished by its support for hybrid geometry backends, including signed distance functions, tetrahedra grids, and volume grids. It employs score distillation sampling to guide the generation process and features a modular plugin system for loading custom modules and nodes. The system covers

TRELLIS is a 3D generative AI model and latent diffusion framework designed to transform natural language descriptions or reference images into textured 3D assets. It operates as a text-to-3D asset generator that utilizes structured latent representations to produce high-quality 3D meshes, Gaussians, and Radiance Fields. The system functions as a multi-format 3D decoder, converting internal representations into standard exchange formats such as GLB and PLY. It also serves as a 3D asset editing tool, enabling the modification of specific regions of generated objects through targeted text or im

Modly is a local AI 3D model generator that converts two-dimensional images into three-dimensional meshes. It is a privacy-focused tool that processes data directly on the host graphics card using GPU-accelerated inference. The system serves as an extensible AI model framework, allowing the integration of external model extensions and runtime files from remote repositories. It utilizes a manifest-driven plugin architecture to add new generation methods by loading metadata and files from external version control systems. The toolset includes a command-line interface for triggering generation

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

Unity MCP is a plugin that connects the Unity Editor to AI assistants through the Model Context Protocol, enabling natural language control over scene manipulation, object creation, and editor workflows. It allows developers to generate C# scripts, modify GameObjects and components, create UI layouts, and manage assets by issuing commands through an AI interface, effectively turning the editor into a conversational development environment. The plugin distinguishes itself through a comprehensive automation system that can execute multi-step tasks from a design document, record and replay edito

This is the PyTorch implementation of the ECCV 2022 paper MeshUDF. We provide one dummy pre-trained UDF network and code for demonstrating our differentiable meshing procedure of open surfaces.

Implicit Geometric Regularization for Learning Shapes

This repository is the official implementation of UCLID-Net: Single View Reconstruction in Object Space (NeurIPS 2020).

This is the implementation of NeurIPS 2020 paper "Generative 3D Part Assembly via Dynamic Graph Learning" created by Jialei Huang , Guanqi Zhan , Qingnan Fan , Kaichun Mo , Lin Shao , Baoquan Chen , Leonidas Guibas and Hao Dong .

Code base of ParSeNet: ECCV 2020.

This repository provides the implementation of SoftFlow on toy dataset and point clouds. Move to each folder, follow the instructions and enjoy the results!

Wenyu Han, Siyuan Xiang, Chenhui Liu, Ruoyu Wang, Chen Feng

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

Chen-Hsuan Lin, Chen Kong, and Simon Lucey AAAI Conference on Artificial Intelligence (AAAI), 2018

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

This is the offical repository of the paper:

Paper @ ArXiv, Video @ Youtube.

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

CO3Dv2: Common Objects In 3D (version 2)

This repository contains code for the ICCV 2021 paper

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

This repository contains pre-trained models and testing code for MarrNet presented at NIPS 2017.

improves over nerf in 360 capture of unbounded scenes

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