Showing 4 open source projects for "direct rendering manager"

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  • 1
    dm_control

    dm_control

    DeepMind's software stack for physics-based simulation

    ...DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo physics. The MuJoCo Python bindings support three different OpenGL rendering backends: EGL (headless, hardware-accelerated), GLFW (windowed, hardware-accelerated), and OSMesa (purely software-based). At least one of these three backends must be available in order render through dm_control. Hardware rendering with a windowing system is supported via GLFW and GLEW. On Linux these can be installed using your distribution's package manager. ...
    Downloads: 0 This Week
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  • 2
    BlenderMCP

    BlenderMCP

    Blender Model Context Protocol Integration

    BlenderMCP is a bridge that connects Blender, a 3D modeling and rendering software, with AI systems like Claude through the Model Context Protocol, enabling direct AI-driven interaction with 3D environments. It allows users to control Blender using natural language prompts, effectively turning AI into a co-creator for 3D modeling, scene construction, and asset manipulation. The system establishes a two-way communication channel between Blender and the AI, where commands can be sent and results retrieved in real time. ...
    Downloads: 3 This Week
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  • 3
    Fast3R

    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...
    Downloads: 0 This Week
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  • 4
    The AI Scientist-v2

    The AI Scientist-v2

    Workshop-Level Automated Scientific Discovery via Agentic Tree Search

    ...The platform is capable of generating original research ideas, designing and executing experiments, analyzing and visualizing results, and producing full academic papers without direct human intervention. It introduces a generalized framework that removes reliance on predefined templates, enabling broader applicability across multiple machine learning domains and more open-ended exploration of research problems. A key innovation is its progressive agentic tree search, which systematically explores experimental paths and is coordinated by an experiment manager agent that guides decision-making. ...
    Downloads: 0 This Week
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