12 citations · 21 across the 7 of their papers we have counts for
11 papers
DiffPose: Multi-hypothesis Human Pose Estimation using Diffusion models
Karl Holmquist, Bastian Wandt
Traditionally, monocular 3D human pose estimation employs a machine learning model to predict the most likely 3D pose for a given input image. However, a single image can be highly…
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection
Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn +1
Industrial defect detection is commonly addressed with anomaly detection (AD) methods where no or only incomplete data of potentially occurring defects is available. This work disc…
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…
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…
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…
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…