53 citations · 54 across the 2 of their papers we have counts for
3 papers
cs.CV2020★ 1 cited
Discrete Point Flow Networks for Efficient Point Cloud Generation
Roman Klokov, Edmond Boyer, Jakob Verbeek
Generative models have proven effective at modeling 3D shapes and their statistical variations. In this paper we investigate their application to point clouds, a 3D shape represent…
cs.CV2019
Probabilistic Reconstruction Networks for 3D Shape Inference from a Single Image
Roman Klokov, Jakob Verbeek, Edmond Boyer
We study end-to-end learning strategies for 3D shape inference from images, in particular from a single image. Several approaches in this direction have been investigated that expl…
cs.CV2017★ 53 cited
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
Li Yi, Lin Shao, Manolis Savva +47
We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database. The benchmark consists of two tasks: part-level segmentation…