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Related Concept Videos

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Light Acquisition

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In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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Related Experiment Video

Updated: May 16, 2025

Fluorescence Recovery after Merging a Droplet to Measure the Two-dimensional Diffusion of a Phospholipid Monolayer
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IllumiDiff: Indoor Illumination Estimation From a Single Image With Diffusion Model.

Shiyuan Shen, Zhongyun Bao, Wenju Xu

    IEEE Transactions on Visualization and Computer Graphics
    |April 1, 2025
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    Summary
    This summary is machine-generated.

    IllumiDiff generates realistic HDR panoramas from single indoor images, improving 3D object rendering. This novel framework enhances illumination and texture details for more lifelike virtual environments.

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    Area of Science:

    • Computer Vision
    • Computer Graphics
    • Artificial Intelligence

    Background:

    • Single indoor image illumination estimation is challenging.
    • Existing methods struggle with realistic illumination and texture details.
    • This limits the realism of rendering embedded 3D objects.

    Purpose of the Study:

    • To present a novel multi-stage framework, IllumiDiff, for indoor illumination estimation.
    • To generate high-quality High Dynamic Range (HDR) panoramas from single, limited field-of-view images.
    • To improve the realism of rendering 3D objects with complex materials.

    Main Methods:

    • Stage I: Estimate illumination conditions and environmental texture from the input image.
    • Stage II: Generate a Low Dynamic Range (LDR) panorama using a conditional panoramic texture diffusion model.
    • Stage III: Reconstruct the LDR panorama to an HDR panorama using estimated illumination conditions.

    Main Results:

    • IllumiDiff successfully generates HDR panoramas from single indoor images.
    • The generated panoramas exhibit realistic illumination distribution and rich texture details.
    • The framework enables impressive rendering results for 3D objects with diverse materials.

    Conclusions:

    • IllumiDiff offers a significant advancement in single indoor image illumination estimation.
    • The framework addresses limitations of previous methods in texture and illumination realism.
    • This approach enhances the fidelity of virtual scene rendering for applications in computer graphics and virtual reality.