2 citations · 4 across the 9 of their papers we have counts for
5 papers · 1 filter
Hierarchical Mesh Transformers with Topology-Guided Pretraining for Morphometric Analysis of Brain Structures
Yujian Xiong, Mohammad Farazi, Yanxi Chen +8
Representation learning on large-scale unstructured volumetric and surface meshes poses significant challenges in neuroimaging, especially when models must incorporate diverse vert…
A Recipe for Geometry-Aware 3D Mesh Transformers
Mohammad Farazi, Yalin Wang
Utilizing patch-based transformers for unstructured geometric data such as polygon meshes presents significant challenges, primarily due to the absence of a canonical ordering and…
AMG: Avatar Motion Guided Video Generation
Zhangsihao Yang, Mengyi Shan, Mohammad Farazi +4
Human video generation task has gained significant attention with the advancement of deep generative models. Generating realistic videos with human movements is challenging in natu…
TetCNN: Convolutional Neural Networks on Tetrahedral Meshes
Mohammad Farazi, Zhangsihao Yang, Wenhui Zhu +2
Convolutional neural networks (CNN) have been broadly studied on images, videos, graphs, and triangular meshes. However, it has seldom been studied on tetrahedral meshes. Given the…
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…