activity
20172024
most citedExtending Unsupervised Neural Image Compression With Supervised Multitask Learning

19 citations · 89 across the 12 of their papers we have counts for

collaborators

21 papers

cs.CV20241 cited

Towards Geographic Inclusion in the Evaluation of Text-to-Image Models

Melissa Hall, Samuel J. Bell, Candace Ross +3

Rapid progress in text-to-image generative models coupled with their deployment for visual content creation has magnified the importance of thoroughly evaluating their performance…

cs.CV202211 cited

ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations

Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero +7

Deep learning vision systems are widely deployed across applications where reliability is critical. However, even today's best models can fail to recognize an object when its pose,…

cs.CV20225 cited

Uncertainty-Driven Active Vision for Implicit Scene Reconstruction

Edward J. Smith, Michal Drozdzal, Derek Nowrouzezahrai +2

Multi-view implicit scene reconstruction methods have become increasingly popular due to their ability to represent complex scene details. Recent efforts have been devoted to impro…

eess.IV20222 cited

On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction

Tim Bakker, Matthew Muckley, Adriana Romero-Soriano +2

Most current approaches to undersampled multi-coil MRI reconstruction focus on learning the reconstruction model for a fixed, equidistant acquisition trajectory. In this paper, we…

cs.LG20213 cited

Parameter Prediction for Unseen Deep Architectures

Boris Knyazev, Michal Drozdzal, Graham W. Taylor +1

Deep learning has been successful in automating the design of features in machine learning pipelines. However, the algorithms optimizing neural network parameters remain largely ha…

cs.CV2021

Instance-Conditioned GAN

Arantxa Casanova, Marlène Careil, Jakob Verbeek +2

Generative Adversarial Networks (GANs) can generate near photo realistic images in narrow domains such as human faces. Yet, modeling complex distributions of datasets such as Image…