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SIGGRAPH 2022: Neural Geometry Processing

SIGGRAPH 2022: Neural Geometry Processing

SIGGRAPH 2022勉強会で使ったスライドです。
https://siggraph.xyz/s2022/

Tatsuya Yatagawa

August 27, 2022
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  1. Neural Geometry Processing
    Tatsuya Yatagawa
    Aug. 27th, 2022
    SIGGRAPH 2022 Paper Reading Seminar

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  2. 6 TOG , 2 Conference Track
    l Dual Octree Graph Networks for Learning Adaptive Volumetric ...
    l DiffusionNet: Discretization Agnostic Learning on Surfaces
    l Neural Dual Contouring
    l Random Walks for Adversarial Meshes
    l PCEDNet: A Lightweight Neural Network for Fast and Interactive ...
    l Self-Sampling for Neural Point Cloud Consolidation
    l ImLoveNet: Misalignment Image-supported Registration Network ...
    l DSG-Net: Learning Disentangled Structure and Geometry ...
    Neural Geometry Processing (8 papers)

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  3. Dual Octree Graph Networks for Learning Adaptive
    Volumetric Shape Representations
    CNN ,

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  4. 1.
    2.
    ,
    3.
    MLP
    Dual Octree Graph

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  5. l , .
    l .

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  6. DiffusionNet: Discretization Agnostic Learning on
    Surfaces

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  7. :
    l 𝑡 ,
    DiffusionNet
    ,
    (= )
    l ,
    : , : +

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  8. ,
    l target
    l , ,
    .
    : , attention .
    , .

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  9. Neural Dual Contouring
    Dual Contouring

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  10. Marching Cubes ( : Dual Contouring, : Marching Cubes)
    Dual Contouring
    Dual Contouring
    ,
    Marching Cubes

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  11. l MC
    (MC )
    l MC ,
    ,
    : Neural Marching Cubes
    l ,
    (= )
    l

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  12. l NMC , DC
    l NMC , DC
    l NDC ,
    UNDC
    l DC
    l UNDC ,
    Neural Dual Contouring

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  13. l ( ) ,
    ,

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  14. Random Walks for Adversarial Meshes (Conf. Track)
    ,

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  15. ,
    (adversarial sample)
    : [Goodfellow et al., ICLR 2015]
    l

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  16. l RandomWalker [Lahav and Tal 2020]
    l
    : Imitating Network

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  17. l , random walk
    l Imitating Net ,
    :

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  18. l , (RandomWalker, MeshNet)
    l Imitating Network
    (Walk path Random Walker )

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  19. PCEDNet: A Lightweight Neural Network for Fast and
    Interactive Edge Detection in 3D Point Clouds

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  20. (Scale-Space Matrix)
    l Growing Least Squares [Mellado+ 2012]
    l , - , , ,
    .
    l 6 ,
    16 (=SSM) .
    PCEDNet (Point Cloud Edge Detection Network)
    l SSM (= 6 16 )
    .

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  21. l
    , ,
    ,
    l MLP, CNN
    l CNN ,
    ,
    l SSM 4-128
    ,
    l ,
    16
    4 16 128

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  22. Self-Sampling for Neural Point Cloud Consolidation
    ,
    Input Consolidated Input Consolidated

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  23. :
    l positive ( ) negative ( ) .
    l , (source)
    (target)
    , positive
    l

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  24. , .
    Input Consolidated Input Consolidated
    : , positive, negative
    , .

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  25. ImLoveNet: Misaligned Image-supported Registration Network
    for Low-overlap Point Cloud Pairs (Conf. Track)
    2

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  26. : , 2
    l (DGR [Choy+ 2020],
    PREDATOR [Huang+ 2021] etc.).
    l
    )

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  27. SOTA (PREDATOR, OMNet)
    : ,
    ,
    .

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  28. DSG-Net: Learning Disentangled Structure and
    Geometry for 3D Shape Generation
    (VAE)

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  29. :
    ,
    .
    :
    .

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  30. l 2
    +
    ( ) ( )
    l as-consistent-as-
    possible (9
    BBox ) [Guo+ 2019]
    l one-hot
    MLP
    l ACAP BBox
    ,
    .

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  31. (SDM-Net) , ,

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  32. 6 TOG , 2 Conference Track
    l Dual Octree Graph Networks for Learning Adaptive Volumetric ...
    l DiffusionNet: Discretization Agnostic Learning on Surfaces
    l Neural Dual Contouring
    l Random Walks for Adversarial Meshes
    l PCEDNet: A Lightweight Neural Network for Fast and Interactive ...
    l Self-Sampling for Neural Point Cloud Consolidation
    l ImLoveNet: Misalignment Image-supported Registration Network ...
    l DSG-Net: Learning Disentangled Structure and Geometry ...
    : Neural Geometry Processing
    : , .
    , (=
    ) .

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