1.2k citations · 2.2k across the 48 of their papers we have counts for
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Needles in Haystacks: On Classifying Tiny Objects in Large Images
Nick Pawlowski, Suvrat Bhooshan, Nicolas Ballas +3
In some important computer vision domains, such as medical or hyperspectral imaging, we care about the classification of tiny objects in large images. However, most Convolutional N…
On the Evaluation of Conditional GANs
Terrance DeVries, Adriana Romero, Luis Pineda +2
Conditional Generative Adversarial Networks (cGANs) are finding increasingly widespread use in many application domains. Despite outstanding progress, quantitative evaluation of su…
Elucidating image-to-set prediction: An analysis of models, losses and datasets
Luis Pineda, Amaia Salvador, Michal Drozdzal +1
In this paper, we identify an important reproducibility challenge in the image-to-set prediction literature that impedes proper comparisons among published methods, namely, researc…
Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition
Zizhao Zhang, Adriana Romero, Matthew J. Muckley +3
The goal of MRI reconstruction is to restore a high fidelity image from partially observed measurements. This partial view naturally induces reconstruction uncertainty that can onl…
The Liver Tumor Segmentation Benchmark (LiTS)
Patrick Bilic, Patrick Christ, Hongwei Bran Li +106
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedi…