Claudio Michaelis

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Universität Tübingen

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. ∙ 0 ∙ share

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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. ∙ 3 ∙ share

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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. ∙ 18 ∙ share

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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. ∙ 4 ∙ share

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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. ∙ 14 ∙ share

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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. ∙ 16 ∙ share

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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. ∙ 0 ∙ share

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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. ∙ 0 ∙ share

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Claudio Michaelis

Featured Co-authors

Matthias Bethge

Richard Zemel

Wieland Brendel

Jörn-Henrik Jacobsen

Georg Martius

Alexander S. Ecker

Ivan Ustyuzhaninov

Robert Geirhos

Felix A. Wichmann

Michal Rolinek

Anselm Paulus

Closing the Generalization Gap in One-Shot Object Detection

Shortcut Learning in Deep Neural Networks

Optimizing Rank-based Metrics with Blackbox Differentiation

Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

One-Shot Instance Segmentation

One-shot Texture Segmentation

One-Shot Segmentation in Clutter