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4DGaussians is a research library and neural rendering engine designed for reconstructing and rendering dynamic three-dimensional scenes. It represents moving environments as a collection of Gaussian primitives that evolve in position and appearance over a temporal dimension. The framework utilizes neural deformation fields to predict spatial offsets and rotations for static point representations, simulating complex motion over time. It further employs temporal basis decomposition to encode motion trajectories into learned functions, compressing dynamic scene data while maintaining smooth tra
Instant-ngp is a high-performance neural graphics engine and toolkit designed for 3D reconstruction and the rendering of neural radiance fields. It provides an integrated framework for generating photorealistic volumetric representations from sets of two-dimensional images by optimizing continuous neural scene models. The project distinguishes itself through a focus on rapid training and real-time inference, achieved by mapping spatial coordinates into compact feature grids. By utilizing multiresolution hash encoding and fused processing kernels, the system minimizes computational overhead an
gsplat is a high-performance differentiable rasterization engine for 3D Gaussian splatting, designed for real-time novel view synthesis from 2D images. It provides a complete pipeline for reconstructing 3D scenes by optimizing differentiable Gaussian representations, training models from COLMAP-processed captures or proprietary device files, and generating new viewpoints through a CUDA-accelerated rendering backend. The framework distinguishes itself through memory-optimized CUDA kernels that reduce training memory usage by up to 4x compared to standard implementations while matching publishe
Meshroom is a node-based photogrammetry software designed to transform collections of two-dimensional images into three-dimensional models and scene geometry. It provides a visual interface for constructing and managing modular data pipelines, allowing users to automate complex computer vision tasks such as feature extraction, depth map estimation, and mesh generation. The software distinguishes itself through a distributed computational framework that dispatches resource-intensive tasks across local hardware or remote render farms. By utilizing a directed acyclic graph execution model, it en
Gaussian Splatting is a computational framework designed to transform sparse sets of two-dimensional photographs into photorealistic, interactive three-dimensional scene representations. The system functions as a reconstruction tool and rendering engine, enabling the conversion of image data into volumetric models that support novel view synthesis.
The main features of graphdeco-inria/gaussian-splatting are: Novel View Synthesis Engines, 3D Rendering Engines, Reconstruction Tools, 3D Reconstruction Pipelines, Radiance Field Engines, Geometry Optimizers, Differentiable Rasterizers, Core Implementations.
Projects with overlapping indexed features include: hustvl/4dgaussians — 4DGaussians is a research library and neural rendering engine designed for reconstructing and rendering dynamic… nvlabs/instant-ngp — Instant-ngp is a high-performance neural graphics engine and toolkit designed for 3D reconstruction and the rendering… nerfstudio-project/gsplat — gsplat is a high-performance differentiable rasterization engine for 3D Gaussian splatting, designed for real-time… alicevision/meshroom — Meshroom is a node-based photogrammetry software designed to transform collections of two-dimensional images into… facebookresearch/pytorch3d — PyTorch3D is a 3D geometric deep learning library and mesh processing toolkit designed for learning from point clouds… nerfies/nerfies.github.io — This project is a computer vision pipeline and volumetric rendering system used to transform photos and videos into…