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The international journal Computer Graphics Forum (CGF) is jointly published by the Eurographics Association and Wiley (former Blackwell). CGF is a leading journal for in-depth technical articles on computer graphics.

  • Interaction Mix and Match: Synthesizing Close Interaction using Conditional Hierarchical GAN with Multi-Hot Class Embedding 

    Goel, Aman; Men, Qianhui; Ho, Edmond S. L. (The Eurographics Association and John Wiley & Sons Ltd., 2022)
    Synthesizing multi-character interactions is a challenging task due to the complex and varied interactions between the characters. In particular, precise spatiotemporal alignment between characters is required in generating ...
  • Context-based Style Transfer of Tokenized Gestures 

    Kuriyama, Shigeru; Mukai, Tomohiko; Taketomi, Takafumi; Mukasa, Tomoyuki (The Eurographics Association and John Wiley & Sons Ltd., 2022)
    Gestural animations in the amusement or entertainment field often require rich expressions; however, it is still challenging to synthesize characteristic gestures automatically. Although style transfer based on a neural ...
  • MP-NeRF: Neural Radiance Fields for Dynamic Multi-person synthesis from Sparse Views 

    Chao, Xian Jin; Leung, Howard (The Eurographics Association and John Wiley & Sons Ltd., 2022)
    Multi-person novel view synthesis aims to generate free-viewpoint videos for dynamic scenes of multiple persons. However, current methods require numerous views to reconstruct a dynamic person and only achieve good performance ...
  • PERGAMO: Personalized 3D Garments from Monocular Video 

    Casado-Elvira, Andrés; Comino Trinidad, Marc; Casas, Dan (The Eurographics Association and John Wiley & Sons Ltd., 2022)
    Clothing plays a fundamental role in digital humans. Current approaches to animate 3D garments are mostly based on realistic physics simulation, however, they typically suffer from two main issues: high computational ...
  • Learning Physics with a Hierarchical Graph Network 

    Chentanez, Nuttapong; Jeschke, Stefan; Müller, Matthias; Macklin, Miles (The Eurographics Association and John Wiley & Sons Ltd., 2022)
    We propose a hierarchical graph for learning physics and a novel way to handle obstacles. The finest level of the graph consist of the particles itself. Coarser levels consist of the cells of sparse grids with successively ...

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