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Anastasia Dubrovina

2 accepted papers

2019

Composite Shape Modeling via Latent Space Factorization

ICCV 2019poster

We present a novel neural network architecture, termed Decomposer-Composer, for semantic structure-aware 3D shape modeling. Our method utilizes an auto-encoder-based pipeline, and produces a novel factorized shape embedding space, where the semantic structure of the shape collection translates into…

Cited by 67PDF ↗Scholar ↗
2019

Supervised Fitting of Geometric Primitives to 3D Point Clouds

CVPR 2019oral

Fitting geometric primitives to 3D point cloud data bridges a gap between low-level digitized 3D data and high-level structural information on the underlying 3D shapes. As such, it enables many downstream applications in 3D data processing. For a long time, RANSAC-based methods have been the gold st…

Cited by 246PDF ↗Scholar ↗