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Nguyen-Phuoc et al., 2018 - Google Patents

Rendernet: A deep convolutional network for differentiable rendering from 3d shapes

Nguyen-Phuoc et al., 2018

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Document ID
2520359496499363195
Author
Nguyen-Phuoc T
Li C
Balaban S
Yang Y
Publication year
Publication venue
Advances in neural information processing systems

External Links

Snippet

Traditional computer graphics rendering pipelines are designed for procedurally generating 2D images from 3D shapes with high performance. The nondifferentiability due to discrete operations (such as visibility computation) makes it hard to explicitly correlate rendering …
Continue reading at proceedings.neurips.cc (PDF) (other versions)

Classifications

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    • G06T15/205Image-based rendering
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/003D [Three Dimensional] image rendering
    • G06T15/50Lighting effects
    • G06T15/60Shadow generation
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    • G06COMPUTING; CALCULATING; COUNTING
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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    • G06T15/06Ray-tracing
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    • G06COMPUTING; CALCULATING; COUNTING
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    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/20Finite element generation, e.g. wire-frame surface description, tesselation
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    • G06T17/10Constructive solid geometry [CSG] using solid primitives, e.g. cylinders, cubes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
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