Search Results for "3d structure"
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Showing 33 open source projects for "3d structure"
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1
SAM 3D Body
Code for running inference with the SAM 3D Body Model 3DB
SAM 3D Body is a promptable model for single-image full-body 3D human mesh recovery, designed to estimate detailed human pose and shape from just one RGB image. It reconstructs the full body, including feet and hands, using the Momentum Human Rig (MHR), a parametric mesh representation that decouples skeletal structure from surface shape for more accurate and interpretable results. -
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MESHROOM
3D reconstruction software
Photogrammetry is the science of making measurements from photographs. It infers the geometry of a scene from a set of unordered photographies or videos. Photography is the projection of a 3D scene onto a 2D plane, losing depth information. The goal of photogrammetry is to reverse this process. The dense modeling of the scene is the result yielded by chaining two computer vision-based pipelines, “Structure-from-Motion” (SfM) and “Multi View Stereo” (MVS). Fusion of Multi-bracketing LDR images into HDR. Alignment of panorama images. ... -
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TRELLIS.2
Native and Compact Structured Latents for 3D Generation
TRELLIS.2 is a cutting-edge open-source model and codebase for high-fidelity 3D asset generation from 2D images, developed to push forward the state of the art in image-to-3D generation. At its core is a novel sparse voxel structure called O-Voxel that jointly encodes both geometry and surface appearance, enabling reconstruction and generation of complex 3D shapes with arbitrary topology, open surfaces, and physically based rendering (PBR) textures. -
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Protenix
A trainable PyTorch reproduction of AlphaFold 3
Protenix is an open-source, trainable PyTorch reimplementation of AlphaFold 3, developed by ByteDance with the goal of democratizing high-accuracy protein structure prediction for computational biology and drug-discovery research. Protenix provides a complete pipeline for turning protein sequences (with optional MSA / sequence alignment) or structural inputs (e.g. PDB/CIF) into full 3D atomic-level structure predictions. It supports both “full” models and lightweight variants such as “Protenix-Mini,” offering a trade-off between speed/compute cost and predictive accuracy — making structure prediction accessible even in resource-constrained environments. ... -
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Depth Anything 3
Recovering the Visual Space from Any Views
Depth Anything 3 is a research-driven project that brings accurate and dense depth estimation to any input image or video, enabling foundational understanding of 3D structure from 2D visual content. Designed to work across diverse scenes, lighting conditions, and image types, it uses advanced neural networks trained on large, heterogeneous datasets, producing depth maps that reveal scene depth relationships and object surfaces with strong fidelity. The model can be applied to photography, AR/VR content creation, robotics perception, and 3D reconstruction workflows, making it versatile across industries and research domains. ... -
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DocArray
The data structure for multimodal data
DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. ... -
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UniMate
UniMate: One Unified Model to Animate Diverse Skeletons
UniMate is a generative motion model that animates rigged 3D assets with different skeletal structures from natural-language prompts. It is designed to handle bipeds, quadrupeds, birds, marine creatures, insects, serpentine rigs, and articulated rigid objects with one unified model. Its topology-aware diffusion transformer conditions generation on skeleton structure rather than requiring a fixed character template. -
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AlohaMini
Open-Source Dual-Arm Mobile Robot with Motorized Lift
AlohaMini is a lightweight self-hostable productivity and note-taking platform designed to help individuals organize thoughts, tasks, and knowledge in a fast, minimal interface that avoids unnecessary complexity. It combines hierarchical notebooks, rich text editing, and tagging, allowing users to structure information the way they think and refine that structure over time. The platform focuses on speed and responsiveness, with a UI that loads instantly and feels smooth even on modest... -
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Fast3R
Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass
Fast3R is Meta AI’s official CVPR 2025 release for “Towards 3D Reconstruction of 1000+ Images in One Forward Pass.” It represents a next-generation feedforward 3D reconstruction model capable of producing dense point clouds and camera poses for hundreds to thousands of images or video frames in a single inference pass—eliminating the need for slow, iterative structure-from-motion pipelines. Built on PyTorch Lightning and extending concepts from DUSt3R and Spann3r, Fast3R unifies multi-view geometry, depth estimation, and camera registration within a single transformer-based architecture. ... -
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LingBot-Map
A feed-forward 3D foundation model for reconstructing scenes
LingBot-Map is a specialized project focused on mapping conversational or linguistic interactions within chatbot or AI-driven systems, providing a structured way to visualize and organize dialogue flows. It is designed to help developers understand how conversations evolve across different states, enabling better debugging and optimization of chatbot behavior. The system emphasizes mapping relationships between intents, responses, and transitions, creating a clear representation of... -
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Map-Anything
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
Map-Anything is a universal, feed-forward transformer for metric 3D reconstruction that predicts a scene’s geometry and camera parameters directly from visual inputs. Instead of stitching together many task-specific models, it uses a single architecture that supports a wide range of 3D tasks—multi-image structure-from-motion, multi-view stereo, monocular metric depth, registration, depth completion, and more. -
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VGGSfM
VGGSfM: Visual Geometry Grounded Deep Structure From Motion
VGGSfM is an advanced structure-from-motion (SfM) framework jointly developed by Meta AI Research (GenAI) and the University of Oxford’s Visual Geometry Group (VGG). It reconstructs 3D geometry, dense depth, and camera poses directly from unordered or sequential images and videos. The system combines learned feature matching and geometric optimization to generate high-quality camera calibrations, sparse/dense point clouds, and depth maps in standard COLMAP format. -
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SmartNode
Visual simulation platform for space-based data backhaul scenarios
smartNode is a visual simulation platform for space-based intelligent relay and satellite data-return scenarios. It models the relationship between satellites, ground stations, relay links, and content-driven task scheduling. The project includes a Python backend and a browser-based frontend, making it suitable for local simulation, teaching, and secondary development. Users can view a three-dimensional space situation, submit data return tasks, and monitor resource states in real time. The... -
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SCAIL
Towards Studio-Grade Character Animation via In-Context Learning of 3D
SCAIL is a project developed by the ZAI Organization, focusing on AI-driven research initiatives. While specific documentation about SCAIL’s exact goals and implementation is limited from the repository context alone, the project appears to be part of a collection of machine learning and AI research tools that facilitate scalable model development, evaluation, or application workflows. Given its listing alongside other ZAI projects like speech recognition and text-to-speech systems, SCAIL... -
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CemCon
Automated SMILES-to-optimized 3D molecular structure converter
CemCon is a desktop application developed for automated batch conversion of SMILES strings into optimized 3D molecular structures. The software is designed to simplify ligand preparation workflows for molecular docking, virtual screening, molecular dynamics simulations, and other Computer-Aided Drug Design (CADD) applications. Developed by Abhijit Reang and Sandip Das under the supervision of Dr. Arabinda Ghosh, Department of Molecular Biology and Bioinformatics, Tripura University,... -
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Fosite - advection problem solver
numerical simulation code for solving transport equations in 1D/2D/3D
Fosite is a generic framework for the numerical solution of hyperbolic conservation laws in generalized orthogonal coordinates. Its main purpose is the simulation of compressible flows in accretion disks. The underlying numerical solution method belongs to the family of unsplit conservative finite volume TVD schemes. The method is 2nd order accurate in space and uses high order Runge-Kutta and multistep schemes for time evolution. In addition to the pure advection code several source terms... -
17
hloc
Visual localization made easy with hloc
This is hloc, a modular toolbox for state-of-the-art 6-DoF visual localization. It implements Hierarchical Localization, leveraging image retrieval and feature matching, and is fast, accurate, and scalable. This codebase won the indoor/outdoor localization challenges at CVPR 2020 and ECCV 2020, in combination with SuperGlue, our graph neural network for feature matching. We provide step-by-step guides to localize with Aachen, InLoc, and to generate reference poses for your own data using... -
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Gym
Toolkit for developing and comparing reinforcement learning algorithms
Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no... -
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AI Atelier
Based on the Disco Diffusion, version of the AI art creation software
Based on the Disco Diffusion, we have developed a Chinese & English version of the AI art creation software "AI Atelier". We offer both Text-To-Image models (Disco Diffusion and VQGAN+CLIP) and Text-To-Text (GPT-J-6B and GPT-NEOX-20B) as options. Making available complete source code of licensed works and modifications, which include larger works using a licensed work, under the same license. Copyright and license notices must be preserved. When a modified version is used to provide a... -
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3d Linear Transformation Visualization
Visualize 3d linear transformations.
A linear transformation is a function from one vector space to another that respects the linear structure of each vector space. For visualizing this we can transform a vector, but it has an obvious problem, because the linear transformation transform the whole space, not just the vector, in other words it transforms the basis vectors thus every vector in the space gets transformed too. That's why i created this app so everyone can see how a transformation matrix change the whole space. -
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DeepSDF
Learning Continuous Signed Distance Functions for Shape Representation
DeepSDF is a deep learning framework for continuous 3D shape representation using Signed Distance Functions (SDFs), as presented in the CVPR 2019 paper DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation by Park et al. The framework learns a continuous implicit function that maps 3D coordinates to their corresponding signed distances from object surfaces, allowing compact, high-fidelity shape modeling. Unlike traditional discrete voxel grids or meshes, DeepSDF... -
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NiftyNet
An open-source convolutional neural networks platform for research
An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging... -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with both RGB and optical flow input streams. ... -
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To create an Open Source and Free solution for the analysis of woven fabric stuctures. Included will be the ability to view the weave structure in 2D, 3D and profile as well as print and save the drafts (patterns).
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Py3DN
Morphometric analysis and visualization of the 3D structure of neurons
...The application was developed in Python and uses Blender (an open source program) to produce detailed 3D representations of raw and processed data. Py3DN is described in the paper: Aguiar P et al, "Versatile morphometric analysis and visualization of the three-dimensional structure of neurons", Neuroinformatics, 2013, 11(4):393-403 doi: 10.1007/s12021-013-9188-z
