[CVPR'23, Highlight] ECON: Explicit Clothed humans Optimized via Normal integration
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Updated
Sep 17, 2024 - Python
[CVPR'23, Highlight] ECON: Explicit Clothed humans Optimized via Normal integration
Eclipse Ditto™: Digital Twin framework of Eclipse IoT - main repository
Open-source and real-time orchestrator for cyber-physical-systems, to easily design, test and deploy embedded applications and digital twins.
Package manager for things. Start designing modular hardware! PartCAD is the standard for documenting manufacturable physical products (a.k.a. Digital Thread or TDP). It comes with a set of tools to maintain product information and to facilitate efficient and effective workflows at all product lifecycle phases, boosted by AI.
Curated repository of awesome Digital Twin resources
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A curated list of resources to see the big picture of XR
An Integrated Cyber-Physical Ecosystem for Autonomous Driving Research and Education
[CVPR 2026] 3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image
Open-source CLI and Agent plugin suite for EverMe — cross-device, cross-Agent personal memory for AI Agents.
WillowTwin open digital twin definition language (DTDL) ontology for buildings and real estate
Sintef Digital Twin
Public repo for DTC Digital Twin Capabilities Toolkit
A curated repository of awesome Digital Twin resources.
TwinGraph is a Python framework for distributed container orchestration using Kubernetes clusters, Docker Compose/Swarm or cloud resources on AWS (AWS Lambda, AWS Batch, Amazon EKS). Applications include high-throughput simulations, simulation-driven optimization, Digital Twins and machine learning.
Plugboard is an event driven modelling and orchestration framework in Python for simulating and driving complex processes with many interconnected stateful components.
B. Sc. Thesis concerning the semi-automatic creation of a digital twin of a traffic scene near Amirkabir University of Technology
A python framework for creating image-guided cancer patient digital twins.
The simulator for education
Multi-Agent Deep Reinforcement Learning for Cooperative and Competitive Autonomous Vehicles
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