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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 67PDFScholar
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 246PDFScholar