2.1k citations · 3.1k across the 8 of their papers we have counts for
8 papers
A Broad Dataset is All You Need for One-Shot Object Detection
Claudio Michaelis, Matthias Bethge, Alexander S. Ecker
Is it possible to detect arbitrary objects from a single example? A central problem of all existing attempts at one-shot object detection is the generalization gap: Object categori…
Shortcut Learning in Deep Neural Networks
Robert Geirhos, Jörn-Henrik Jacobsen, Claudio Michaelis +4
Deep learning has triggered the current rise of artificial intelligence and is the workhorse of today's machine intelligence. Numerous success stories have rapidly spread all over…
Optimizing Rank-based Metrics with Blackbox Differentiation
Michal Rolínek, Vít Musil, Anselm Paulus +3
Rank-based metrics are some of the most widely used criteria for performance evaluation of computer vision models. Despite years of effort, direct optimization for these metrics re…
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
Claudio Michaelis, Benjamin Mitzkus, Robert Geirhos +5
The ability to detect objects regardless of image distortions or weather conditions is crucial for real-world applications of deep learning like autonomous driving. We here provide…
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos, Patricia Rubisch, Claudio Michaelis +3
Convolutional Neural Networks (CNNs) are commonly thought to recognise objects by learning increasingly complex representations of object shapes. Some recent studies suggest a more…
One-Shot Instance Segmentation
Claudio Michaelis, Ivan Ustyuzhaninov, Matthias Bethge +1
We tackle the problem of one-shot instance segmentation: Given an example image of a novel, previously unknown object category, find and segment all objects of this category within…
One-shot Texture Segmentation
Ivan Ustyuzhaninov, Claudio Michaelis, Wieland Brendel +1
We introduce one-shot texture segmentation: the task of segmenting an input image containing multiple textures given a patch of a reference texture. This task is designed to turn t…
One-Shot Segmentation in Clutter
Claudio Michaelis, Matthias Bethge, Alexander S. Ecker
We tackle the problem of one-shot segmentation: finding and segmenting a previously unseen object in a cluttered scene based on a single instruction example. We propose a novel dat…