research
∙
04/20/2023
ReLight My NeRF: A Dataset for Novel View Synthesis and Relighting of Real World Objects
In this paper, we focus on the problem of rendering novel views from a N...
share
research
∙
02/10/2023
Deep Learning on Implicit Neural Representations of Shapes
Implicit Neural Representations (INRs) have emerged in the last few year...
research
∙
10/15/2022
Self-Distillation for Unsupervised 3D Domain Adaptation
Point cloud classification is a popular task in 3D vision. However, prev...
research
∙
10/21/2021
RefRec: Pseudo-labels Refinement via Shape Reconstruction for Unsupervised 3D Domain Adaptation
Unsupervised Domain Adaptation (UDA) for point cloud classification is a...
research
∙
06/06/2021
Go with the Flows: Mixtures of Normalizing Flows for Point Cloud Generation and Reconstruction
Recently normalizing flows (NFs) have demonstrated state-of-the-art perf...
research
∙
11/17/2020
A Divide et Impera Approach for 3D Shape Reconstruction from Multiple Views
Estimating the 3D shape of an object from a single or multiple images ha...
research
∙
11/06/2020
Learning to Orient Surfaces by Self-supervised Spherical CNNs
Defining and reliably finding a canonical orientation for 3D surfaces is...
research
∙
11/06/2019
Boosting Object Recognition in Point Clouds by Saliency Detection
Object recognition in 3D point clouds is a challenging task, mainly when...
research
∙
09/15/2019
Learning an Effective Equivariant 3D Descriptor Without Supervision
Establishing correspondences between 3D shapes is a fundamental task in ...
research
∙
09/15/2019
Performance Evaluation of Learned 3D Features
Matching surfaces is a challenging 3D Computer Vision problem typically ...
research
∙
07/22/2017
