94 citations · 431 across the 15 of their papers we have counts for
5 papers · 1 filter
UNIST: Unpaired Neural Implicit Shape Translation Network
Qimin Chen, Johannes Merz, Aditya Sanghi +3
We introduce UNIST, the first deep neural implicit model for general-purpose, unpaired shape-to-shape translation, in both 2D and 3D domains. Our model is built on autoencoding imp…
Learning Mesh Representations via Binary Space Partitioning Tree Networks
Zhiqin Chen, Andrea Tagliasacchi, Hao Zhang
Polygonal meshes are ubiquitous, but have only played a relatively minor role in the deep learning revolution. State-of-the-art neural generative models for 3D shapes learn implici…
Neural Marching Cubes
Zhiqin Chen, Hao Zhang
We introduce Neural Marching Cubes (NMC), a data-driven approach for extracting a triangle mesh from a discretized implicit field. Classical MC is defined by coarse tessellation te…
CAPRI-Net: Learning Compact CAD Shapes with Adaptive Primitive Assembly
Fenggen Yu, Zhiqin Chen, Manyi Li +4
We introduce CAPRI-Net, a neural network for learning compact and interpretable implicit representations of 3D computer-aided design (CAD) models, in the form of adaptive primitive…
RaidaR: A Rich Annotated Image Dataset of Rainy Street Scenes
Jiongchao Jin, Arezou Fatemi, Wallace Lira +5
We introduce RaidaR, a rich annotated image dataset of rainy street scenes, to support autonomous driving research. The new dataset contains the largest number of rainy images (58,…