Multiscale Centerline Detection

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Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of the ...

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

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Multiscale Centerline Detection

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Enabling Uncertainty Estimation in Iterative Neural Networks

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Aggregating Spatial and Photometric Context for Photometric Stereo

Incorporating Projective Geometry into Deep Learning

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Monitoring Outdoor Parking in Urban Areas With Unmanned Aerial Vehicles

At what spatial scale does natural selection operate? Using multiscale frameworks to calibrate the effects of environmental factors across landscape continuums

Text as a Richer Source of Supervision in Semantic Segmentation Tasks

Detecting Anomalies and Obstacles in Road Scenes

Deep Learning for 3D Surface Modelling and Reconstruction

Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

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

swissALPS: a Dataset for Imbalanced Land Cover Mapping in Alpine Regions

Improving Object Detection under Domain Shifts

Weakly supervised joint whole-slide segmentation and classification in prostate cancer

Automated image-based generation of finite element models for masonry buildings

Digital twins for post-earthquake damage assessment of free-standing buildings including damage information

Learning to Represent and Reconstruct 3D Deformable Objects

Object Priors for Volumetric Image Segmentation

Graph Representation Learning in Computational Pathology