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[CVPR 2025] MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction Priors
PyTorch implementation for SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
Official Implementation for "Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures"
mcp-use is the easiest way to interact with mcp servers with custom agents
[CVPR 2025 Best Paper Award] VGGT: Visual Geometry Grounded Transformer
Pixel-Aligned Recurrent Queries for Multi-View 3D Object Detection (ICCV23)
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
Light Vanilla Javascript library to compare multiples images with sliders. Also, you can add text and filters to your images.
Code accompanying the paper "Generalized Interpolating Discrete Diffusion"
A python tool for fitting primitives 3D shapes in point clouds using RANSAC algorithm
Python implementation of Levenberg-Marquardt algorithm built from scratch using NumPy.
GeoCalib: Learning Single-image Calibration with Geometric Optimization (ECCV 2024)
A project page template for academic papers. Demo at https://eliahuhorwitz.github.io/Academic-project-page-template/
Implementation of the Point Transformer layer, in Pytorch
PyViz3D is a web-based visualizer for 3D objects and point clouds.
This repository contains the code for the paper "Occupancy Networks - Learning 3D Reconstruction in Function Space"
[ICLR 2025] From anything to mesh like human artists. Official impl. of "MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers"
This repo is a PyTorch implementation for Paper "Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds"
MeshGPT: Generating Triangle Meshes with Decoder-Only Transformers
[ICLR 2024] OpenSet 3D Neural Scene Segmentation with Pixel-wise Features and Rendered Novel Views
[CVPR'24] NeRF On-the-go: Exploiting Uncertainty for Distractor-free NeRFs in the Wild
Source code and Dataset creation for the paper "Neural Symbolic Regression That Scales"
[NeurIPS 2023] Code for "Differentiable Blocks World: Qualitative 3D Decomposition by Rendering Primitives"