Now showing items 1-3 of 3

    • Generating 3D Faces using Multi-column Graph Convolutional Networks 

      Li, Kun; Liu, Jingying; Lai, Yu-Kun; Yang, Jingyu (The Eurographics Association and John Wiley & Sons Ltd., 2019)
      In this work, we introduce multi-column graph convolutional networks (MGCNs), a deep generative model for 3D mesh surfaces that effectively learns a non-linear facial representation. We perform spectral decomposition of ...
    • An Image-based Approach for Detecting Faces Carved in Heritage Monuments 

      Lai, Yu-Kun; Echavarria, Karina Rodriguez; Song, Ran; Rosin, Paul L. (The Eurographics Association, 2018)
      Heritage monuments such as columns, memorials and buildings are typically carved with a variety of visual features, including figural content, illustrating scenes from battles or historical narratives. Understanding such ...
    • SHREC 2020 Track: Non-rigid Shape Correspondence of Physically-Based Deformations 

      Dyke, Roberto M.; Zhou, Feng; Lai, Yu-Kun; Rosin, Paul L.; Guo, Daoliang; Li, Kun; Marin, Riccardo; Yang, Jingyu (The Eurographics Association, 2020)
      Commonly, novel non-rigid shape correspondence techniques focus on particular matching challenges. This can lead to the potential trade-off of poorer performance in other scenarios. An ideal dataset would provide a granular ...