Now showing items 1-2 of 2

    • Learning Part Boundaries from 3D Point Clouds 

      Loizou, Marios; Averkiou, Melinos; Kalogerakis, Evangelos (The Eurographics Association and John Wiley & Sons Ltd., 2020)
      We present a method that detects boundaries of parts in 3D shapes represented as point clouds. Our method is based on a graph convolutional network architecture that outputs a probability for a point to lie in an area that ...
    • PriFit: Learning to Fit Primitives Improves Few Shot Point Cloud Segmentation 

      Sharma, Gopal; Dash, Bidya; RoyChowdhury, Aruni; Gadelha, Matheus; Loizou, Marios; Cao, Liangliang; Wang, Rui; Learned-Miller, Erik G.; Maji, Subhransu; Kalogerakis, Evangelos (The Eurographics Association and John Wiley & Sons Ltd., 2022)
      We present PRIFIT, a semi-supervised approach for label-efficient learning of 3D point cloud segmentation networks. PRIFIT combines geometric primitive fitting with point-based representation learning. Its key idea is to ...