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The German physicist Heinrich Hertz (1857–1894) was the first to generate and detect certain types of electromagnetic waves in the laboratory. Starting in 1887, he performed a series of experiments that confirmed the existence of electromagnetic waves and verified that they travel at the speed of light. Hertz used an alternating-current RLC (resistor-inductor-capacitor) circuit that resonated at a known frequency and connected it to a loop of wire. High voltages induced across the gap in...
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The average temperature of Earth is the subject of much current discussion. Earth is in radiative contact with both the Sun and dark space; it receives almost all its energy from the radiation of the Sun and reflects some of it into outer space. Dark space is very cold, about 3 K, so Earth radiates energy into it. For instance, heat transfer occurs from soil and grasses, the rate of which can be so rapid that frost can occur on clear summer evenings, even in warm latitudes.
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Updated: May 23, 2025

Localizing Protein in 3D Neural Stem Cell Culture: a Hybrid Visualization Methodology
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GO-NeRF: Generating Objects in Neural Radiance Fields for Virtual Reality Content Creation.

Peng Dai, Feitong Tan, Xin Yu

    IEEE Transactions on Visualization and Computer Graphics
    |March 10, 2025
    PubMed
    Summary
    This summary is machine-generated.

    GO-NeRF enables intuitive 3D object creation within existing scenes for virtual environments. This novel pipeline seamlessly integrates user-generated objects, enhancing virtual, augmented, and mixed reality experiences.

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    Area of Science:

    • Computer Graphics
    • Virtual Reality
    • 3D Scene Reconstruction

    Background:

    • Virtual environments (VEs) are crucial for virtual, augmented, and mixed reality (VR/AR/MR).
    • Creating 3D objects directly within established 3D scenes (NeRFs) for novel VE generation is an underexplored area.
    • Seamless integration of new 3D objects into existing scenes presents significant challenges.

    Purpose of the Study:

    • To introduce a novel pipeline, GO-NeRF, for intuitive 3D object generation within existing 3D scenes.
    • To enable the creation of high-quality 3D objects and their seamless integration into NeRF-represented scenes.
    • To leverage scene context for generating objects that harmonize with their surroundings.

    Main Methods:

    • Utilizing text prompts and user-specified regions as input for 3D object generation.
    • Employing a compositional rendering formulation with 3D-aware opacity maps for scene integration.
    • Developing tailored optimization objectives and training strategies to mitigate artifacts and capture scene context.

    Main Results:

    • Demonstrated superior performance in generating harmonized 3D objects within surrounding scenes.
    • Successfully synthesized high-quality novel view images for both forward-facing and 360° scenes.
    • Mitigated common artifacts like 'floaters' during object optimization within the scene.

    Conclusions:

    • GO-NeRF offers an effective solution for creating and integrating 3D objects into existing NeRF scenes.
    • The method enhances the creation of novel virtual environments for VR/AR/MR applications.
    • The approach shows significant potential for advancing 3D content creation in immersive technologies.