5 papers · 1 filter
Nexus: Native Mesh Generation with Diffusion
Hanxiao Wang, Ying-Tian Liu, Yuan-Chen Guo +5
Generating high-quality triangle meshes is essential for film, gaming, and interactive 3D applications. Mainstream methods rely on mesh serialization and autoregressive processes,…
FACE: A Face-based Autoregressive Representation for High-Fidelity and Efficient Mesh Generation
Hanxiao Wang, Yuan-Chen Guo, Ying-Tian Liu +6
Autoregressive models for 3D mesh generation suffer from a fundamental limitation: they flatten meshes into long vertex-coordinate sequences. This results in prohibitive computatio…
iFlame: Interleaving Full and Linear Attention for Efficient Mesh Generation
Hanxiao Wang, Biao Zhang, Weize Quan +2
This paper propose iFlame, a novel transformer-based network architecture for mesh generation. While attention-based models have demonstrated remarkable performance in mesh generat…
Autoregressive Generation of Static and Growing Trees
Hanxiao Wang, Biao Zhang, Jonathan Klein +3
We propose a transformer architecture and training strategy for tree generation. The architecture processes data at multiple resolutions and has an hourglass shape, with middle lay…
E-Net: Efficient E(3)-Equivariant Normal Estimation Network
Hanxiao Wang, Mingyang Zhao, Weize Quan +3
Point cloud normal estimation is a fundamental task in 3D geometry processing. While recent learning-based methods achieve notable advancements in normal prediction, they often ove…