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Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines. While...
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Different notations are used to represent the three-dimensional structure of molecules on two-dimensional surfaces. One of the most commonly used representations is the dash-wedge formula. The dashed wedges, solid wedges, and the plane lines indicate the groups situated behind the plane, coming out of the plane, and in the plane, respectively.
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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
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GS-ProCams: Gaussian Splatting-Based Projector-Camera Systems.

Qingyue Deng, Jijiang Li, Haibin Ling

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    Summary
    This summary is machine-generated.

    GS-ProCams introduces Gaussian Splatting for projector-camera systems, enabling efficient, view-agnostic projection mapping. This novel framework significantly improves speed and reduces memory usage compared to previous methods.

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    Area of Science:

    • Computer Vision
    • Computer Graphics
    • Robotics

    Background:

    • Projector-camera systems (ProCams) are crucial for applications requiring precise spatial mapping.
    • Existing methods like CNN-based ProCams are viewpoint-dependent, while NeRF-based ProCams require extra hardware and are computationally intensive.

    Purpose of the Study:

    • To develop a novel framework for view-agnostic projection mapping using Gaussian Splatting.
    • To enhance the efficiency and reduce the resource requirements of ProCams.

    Main Methods:

    • Introduced GS-ProCams, a framework utilizing 2D Gaussian representations for scene modeling.
    • Explicitly modeled geometric and photometric mappings using projector responses, surface properties, and global illumination.
    • Employed differentiable physically-based rendering for joint estimation from multi-view projections.

    Main Results:

    • Achieved superior ProCams simulation quality compared to state-of-the-art NeRF-based methods.
    • Reduced GPU memory usage by 10x during training.
    • Increased inference speed by 900x.

    Conclusions:

    • GS-ProCams offers an efficient and effective solution for view-agnostic projection mapping.
    • The framework eliminates the need for additional light sources, simplifying ProCams setups.
    • This approach significantly advances the performance and accessibility of ProCams applications.