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20192024
most citedAsymmetric Student-Teacher Networks for Industrial Anomaly Detection

12 citations · 21 across the 10 of their papers we have counts for

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9 papers · 1 filter

cs.CV2024

Utilizing Uncertainty in 2D Pose Detectors for Probabilistic 3D Human Mesh Recovery

Tom Wehrbein, Marco Rudolph, Bodo Rosenhahn +1

Monocular 3D human pose and shape estimation is an inherently ill-posed problem due to depth ambiguities, occlusions, and truncations. Recent probabilistic approaches learn a distr…

cs.CV2024

SplatPose & Detect: Pose-Agnostic 3D Anomaly Detection

Mathis Kruse, Marco Rudolph, Dominik Woiwode +1

Detecting anomalies in images has become a well-explored problem in both academia and industry. State-of-the-art algorithms are able to detect defects in increasingly difficult set…

cs.CV2023★ 1 cited

Q-SENN: Quantized Self-Explaining Neural Networks

Thomas Norrenbrock, Marco Rudolph, Bodo Rosenhahn

Explanations in Computer Vision are often desired, but most Deep Neural Networks can only provide saliency maps with questionable faithfulness. Self-Explaining Neural Networks (SEN…

cs.CV2023★ 4 cited

Take 5: Interpretable Image Classification with a Handful of Features

Thomas Norrenbrock, Marco Rudolph, Bodo Rosenhahn

Deep Neural Networks use thousands of mostly incomprehensible features to identify a single class, a decision no human can follow. We propose an interpretable sparse and low dimens…

cs.CV2022

Semantic Segmentation for Fully Automated Macrofouling Analysis on Coatings after Field Exposure

Lutz M. K. Krause, Emily Manderfeld, Patricia Gnutt +8

Biofouling is a major challenge for sustainable shipping, filter membranes, heat exchangers, and medical devices. The development of fouling-resistant coatings requires the evaluat…

cs.CV2021★ 2 cited

Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection

Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn +1

In industrial manufacturing processes, errors frequently occur at unpredictable times and in unknown manifestations. We tackle the problem of automatic defect detection without req…

cs.CV2021

Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows

Tom Wehrbein, Marco Rudolph, Bodo Rosenhahn +1

3D human pose estimation from monocular images is a highly ill-posed problem due to depth ambiguities and occlusions. Nonetheless, most existing works ignore these ambiguities and…

cs.CV2020

CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the Wild

Bastian Wandt, Marco Rudolph, Petrissa Zell +2

Human pose estimation from single images is a challenging problem in computer vision that requires large amounts of labeled training data to be solved accurately. Unfortunately, fo…

cs.CV2020★ 2 cited

Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows

Marco Rudolph, Bastian Wandt, Bodo Rosenhahn

The detection of manufacturing errors is crucial in fabrication processes to ensure product quality and safety standards. Since many defects occur very rarely and their characteris…