47 citations · 53 across the 4 of their papers we have counts for
8 papers
ALTO: Alternating Latent Topologies for Implicit 3D Reconstruction
Zhen Wang, Shijie Zhou, Jeong Joon Park +5
This work introduces alternating latent topologies (ALTO) for high-fidelity reconstruction of implicit 3D surfaces from noisy point clouds. Previous work identifies that the spatia…
ATISS: Autoregressive Transformers for Indoor Scene Synthesis
Despoina Paschalidou, Amlan Kar, Maria Shugrina +3
The ability to synthesize realistic and diverse indoor furniture layouts automatically or based on partial input, unlocks many applications, from better interactive 3D tools to dat…
Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks
Despoina Paschalidou, Angelos Katharopoulos, Andreas Geiger +1
Impressive progress in 3D shape extraction led to representations that can capture object geometries with high fidelity. In parallel, primitive-based methods seek to represent obje…
Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image
Despoina Paschalidou, Luc van Gool, Andreas Geiger
Humans perceive the 3D world as a set of distinct objects that are characterized by various low-level (geometry, reflectance) and high-level (connectivity, adjacency, symmetry) pro…
Superquadrics Revisited: Learning 3D Shape Parsing beyond Cuboids
Despoina Paschalidou, Ali Osman Ulusoy, Andreas Geiger
Abstracting complex 3D shapes with parsimonious part-based representations has been a long standing goal in computer vision. This paper presents a learning-based solution to this p…
RayNet: Learning Volumetric 3D Reconstruction with Ray Potentials
Despoina Paschalidou, Ali Osman Ulusoy, Carolin Schmitt +2
In this paper, we consider the problem of reconstructing a dense 3D model using images captured from different views. Recent methods based on convolutional neural networks (CNN) al…