12 citations · 18 across the 5 of their papers we have counts for
5 papers
Anisotropic Multi-Scale Graph Convolutional Network for Dense Shape Correspondence
Mohammad Farazi, Wenhui Zhu, Zhangsihao Yang +1
This paper studies 3D dense shape correspondence, a key shape analysis application in computer vision and graphics. We introduce a novel hybrid geometric deep learning-based model…
Continuous Geodesic Convolutions for Learning on 3D Shapes
Zhangsihao Yang, Or Litany, Tolga Birdal +2
The majority of descriptor-based methods for geometric processing of non-rigid shape rely on hand-crafted descriptors. Recently, learning-based techniques have been shown effective…
3D Shape Synthesis for Conceptual Design and Optimization Using Variational Autoencoders
Wentai Zhang, Zhangsihao Yang, Haoliang Jiang +5
We propose a data-driven 3D shape design method that can learn a generative model from a corpus of existing designs, and use this model to produce a wide range of new designs. The…
3D Conceptual Design Using Deep Learning
Zhangsihao Yang, Haoliang Jiang, Zou Lan
This article proposes a data-driven methodology to achieve a fast design support, in order to generate or develop novel designs covering multiple object categories. This methodolog…
Data-driven Upsampling of Point Clouds
Wentai Zhang, Haoliang Jiang, Zhangsihao Yang +3
High quality upsampling of sparse 3D point clouds is critically useful for a wide range of geometric operations such as reconstruction, rendering, meshing, and analysis. In this pa…