Projects sharing features with LichtFeld Studio

ComfyUI-3D-Pack is a suite of custom nodes for ComfyUI that enables 3D asset generation and rendering within a node-based workflow. It provides a set of tools for reconstructing textured three-dimensional meshes and volumetric scenes from single images, multi-view images, or text prompts. The system includes a Gaussian splatting generator for creating high-fidelity volumetric 3D scene representations and a multi-view image generator to produce consistent image sets for reconstruction. It also features a single image 3D mesh tool to build geometry from a single 2D source. The toolset covers 3

Genesis is an embodied AI simulation platform and parallelized robotics simulator designed for training general-purpose robotic agents. It integrates a physics engine for robotics that calculates collisions and movements for rigid bodies, soft tissues, and fluids, alongside a photorealistic 3D rendering engine. The platform features a domain randomization framework to vary environment parameters across parallel simulations, aiding in sim-to-real transfer. It supports the integration of real-world captured light fields and Gaussian splatting to provide photorealistic backgrounds within simulat

Supersplat is a web-based suite for editing, optimizing, and viewing 3D Gaussian Splats. It functions as a visual editor for cleaning scenes and a converter for transforming splat data between different file formats to ensure compatibility across tools. The project provides specialized capabilities for 3D scene curation, allowing the configuration of cameras, animations, and annotations. It includes a data optimizer that compresses large spatial datasets into streamed formats to improve loading speeds on web pages. The system further supports the publishing of processed assets to a public ga

few-shot gaussian splatting pipeline

Train, inspect, edit, automate, and export 3D Gaussian Splatting scenes from a single native application.

Nerfstudio is a modular development framework for training, visualizing, and exporting three-dimensional scene representations derived from two-dimensional image datasets. It provides a neural scene reconstruction pipeline that converts raw images and camera data into high-fidelity 3D assets and cinematic video using a differentiable volumetric renderer. The system features an interactive web-based visualizer that allows users to monitor training progress and inspect neural scene geometry in real time. It decouples neural network architectures from the training loop through a standardized mod

ICLR 2025 Oral On Scaling Up 3D Gaussian Splatting Training