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Closing the Generalization Gap in One-Shot Object Detection
Despite substantial progress in object detection and few-shot learning, ...
11/09/2020 ∙ by Claudio Michaelis, et al. ∙
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Shortcut Learning in Deep Neural Networks
Deep learning has triggered the current rise of artificial intelligence ...
04/16/2020 ∙ by Robert Geirhos, et al. ∙
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Optimizing Rank-based Metrics with Blackbox Differentiation
Rank-based metrics are some of the most widely used criteria for perform...
12/07/2019 ∙ by Michal Rolinek, et al. ∙
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Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
The ability to detect objects regardless of image distortions or weather...
07/17/2019 ∙ by Claudio Michaelis, et al. ∙
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ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Convolutional Neural Networks (CNNs) are commonly thought to recognise o...
11/29/2018 ∙ by Robert Geirhos, et al. ∙
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One-Shot Instance Segmentation
We tackle one-shot visual search by example for arbitrary object categor...
11/28/2018 ∙ by Claudio Michaelis, et al. ∙
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One-shot Texture Segmentation
We introduce one-shot texture segmentation: the task of segmenting an in...
07/07/2018 ∙ by Ivan Ustyuzhaninov, et al. ∙
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One-Shot Segmentation in Clutter
We tackle the problem of one-shot segmentation: finding and segmenting a...
03/26/2018 ∙ by Claudio Michaelis, et al. ∙
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