Resolving Ambiguities in Monocular 3D Reconstruction of Deformable Surfaces

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In the context of automatic visual inspection of infrastructures by drones, Deep Learning (DL) models are used to automatically process images for fault diagnostics. While explainable Artificial Intelligence (AI) algorithms can provide explanations to asse ...

Resolving Ambiguities in Monocular 3D Reconstruction of Deformable Surfaces

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Aggregating Spatial and Photometric Context for Photometric Stereo

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Semantic Shape Editing with Parametric Implicit Templates

Enabling Uncertainty Estimation in Iterative Neural Networks

3D diffractive optics for linear interconnects and nonlinear processing

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Multimaterial Volumetric Printing of Silica-Based Glasses

Incorporating Projective Geometry into Deep Learning

Airborne sensor fusion: Expected accuracy and behavior of a concurrent adjustment

An adaptive phase field approach to 3D internal crack growth in rocks

Tool Developments in the OpenMC Code: Correlated Sampling and Transient Fission Matrix Approach Coupled to OpenFOAM

A method and system for enforcing smoothness constraints on surface meshes from a graph convolutional neural network

Deep Learning for 3D Surface Modelling and Reconstruction

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Automated post-earthquake damage assessment of stone masonry buildings integrating machine learning, computer vision, and physics-based modeling

State of the Art in Dense Monocular Non-Rigid 3D Reconstruction

A Full-Wave Reference Simulator for Computing Surface Reflectance

Region Extraction in Mesh Intersection

Exploiting Explanations to Detect Misclassifications of Deep Learning Models in Power Grid Visual Inspection