I am an Assistant Professor at the Linköping University in the Computer Vision Lab (CVL)

My main research interests are human motion capture and 3D reconstruction. A special focus lies on the application of machine learning techniques such as deep learning, dimensionality reduction and compressed sensing. My current research analyses weakly supervised training of deep neural networks for human pose reconstruction and physics-integration into neural networks.

From 2021 to 2022 I was a PostDoc at the University of British Columbia in the group of Helge Rhodin. From 2015 to 2020 I was working as a PhD student at the Leibniz University of Hannover. 



Human Pose Estimation

Physics and Simulations

Anomaly Detection

Unsupervised Machine Learning


Check Google Scholar for a complete list.


*NEW* Pose Modulated Avatars from Videos
Chunjin Song, Bastian Wandt, Helge Rhodin
ICLR 2024

*NEW* Mirror-aware Neural Humans
Daniel Ajisafe, James Tang, Shih-Yang Su, Bastian Wandt, Helge Rhodin
3DV 2024


GMSF: Global Matching Scene Flow
Yushan Zhang, Johan Edstedt, Bastian Wandt, Per-Erik Forssén, Maria Magnusson, Michael Felsberg
NeurIPS 2023

The voraus-AD Dataset for Anomaly Detection in Robot Applications
Jan-Thieß Brockmann, Marco Rudolph, Bodo Rosenhahn, Bastian Wandt
Transactions on Robotics 2023

DiffPose: Multi-hypothesis Human Pose Estimation using Diffusion models *Oral*
Karl Holmquist, Bastian Wandt
ICCV 2023

Deep learning-based 2D keypoint detection in alpine ski racing – A performance analysis of state-of-the-art algorithms applied to regular skiing and injury situations
Michael Zwölfer, Dieter Heinrich, Kurt Schindelwig, Bastian Wandt, Helge Rhodin, Jörg Spörri, Werner Nachbauer
JSAMS 2023

LatentKeypointGAN: Controlling GANs via Latent Keypoints *Best paper*
Xingzhe He, Bastian Wandt, Helge Rhodin
CRV 2023

Asymmetric Student-Teacher Networks for Industrial Anomaly Detection
Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn, Bastian Wandt
WACV 2023

AudioViewer: Learning to Visualize Sound 
Chunjin Song, Yuchi Zhang, Willis Peng, Parmis Mohaghegh, Bastian Wandt, Helge Rhodin,
WACV 2023


AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints *SPOTLIGHT*,
Xingzhe He, Bastian Wandt, Helge Rhodin
NeurIPS 2022
[pdf] [project page]

ElePose: Unsupervised 3D Human Pose Estimation by Predicting Camera Elevation and Learning Normalizing Flows on 2D Poses,
Bastian Wandt, Jim Little, Helge Rhodin
CVPR 2022

AdaptPose: Cross-Dataset Adaptation for 3D Human Pose Estimation by Learnable Motion Generation,
Mohsen Gholami, Bastian Wandt, Helge Rhodin, Rabab Ward, Z. Jane Wang
CVPR 2022

GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation,
Xingzhe He, Bastian Wandt, Helge Rhodin
CVPR 2022

Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection,
Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn, Bastian Wandt
WACV 2022
[pdf] [code]


Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows,
Tom Wehrbein, Marco Rudolph, Bodo Rosenhahn, Bastian Wandt
ICCV 2021
[pdf] [code]

CanonPose: Self-supervised Monocular 3D Human Pose Estimation in the Wild
Bastian Wandt, Marco Rudolph, Helge Rhodin, Bodo Rosenhahn
CVPR 2021
[pdf] [code]

Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows
Marco Rudolph, Bastian Wandt, Bodo Rosenhahn
WACV 2021
[pdf] [code]


Weakly-supervised Learning of Human Dynamics
Petrissa Zell, Bodo Rosenhahn, Bastian Wandt
ECCV 2020


Structuring Autoencoders
Marco Rudolph, Bastian Wandt, Bodo Rosenhahn
ICCV 2019 Workshops

RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation
Bastian Wandt and Bodo Rosenhahn
CVPR 2019
 [pdf, code]


Region-based Cycle-Consistent Data Augmentation for Object Detection
Florian Kluger, Christoph Reinders, Kevin Raetz, Philipp Schelske, Bastian Wandt, Hanno Ackermann, Bodo Rosenhahn
BigData 2018 Road Damage Detection Challenge (Special Award)

A Kinematic Chain Space for Monocular Motion Capture
Bastian Wandt, Hanno Ackermann, Bodo Rosenhahn
ECCV 2018 Workshops

Extending HEVC with a Texture Synthesis Framework using Detail-aware Image Decomposition
Bastian Wandt, Thorsten Laude, Bodo Rosenhahn, Jörn Ostermann
PCS 2018

Detail-aware Image Decomposition for an HEVC-based Texture Synthesis Framework
Bastian Wandt, Thorsten Laude, Bodo Rosenhahn, Jörn Ostermann
DCC 2018

Physics-based Models for Human Gait Analysis
Petrissa Zell, Bastian Wandt, Bodo Rosenhahn
Handbook of Human Motion, Springer International Publishing, 2018


Extending HEVC Using Texture Synthesis
Bastian Wandt, Thorsten Laude, Yiqun Liu, Bodo Rosenhahn, Jörn Ostermann
VCIP 2017

Optical Flow-based 3D Human Motion Estimation from Monocular Video
Thiemo Alldieck, Marc Kassubeck, Bastian Wandt, Bodo Rosenhahn, Marcus Magnor
GCPR 2017

Joint 3D Human Motion Capture and Physical Analysis from Monocular Videos
Petrissa Zell, Bastian Wandt, Bodo Rosenhahn
CVPR 2017 Workshops


3D Reconstruction of Human Motion from Monocular Image Sequences
Bastian Wandt, Hanno Ackermann, Bodo Rosenhahn
TPAMI 2016



Machine Learning (at University of British Columbia, Okanagan Campus)


Machine Learning (at TNT, Hannover)
Bodo Rosenhahn and Bastian Wandt


Tracking and Matching in Image Sequences (at TNT, Hannover)
Bodo Rosenhahn and Bastian Wandt

Master and Bachelor theses

  • Klassifikation menschlicher Bewegungen in Unterräumen (2017)
  • Modellierung eines Posenraums menschlicher Bewegungen mit Hilfe neuronaler Netze (2017)
  • Representation of Human Motion using Neural Networks (2018)
  • Codierung menschlicher Oberflächenmodelle mittels Neuronaler Netze (2018)
  • Zeitkonsistente Schätzung Menschlicher Posen mittels Neuronaler Netze (2018)
  • Recurrent Neural Networks for Monocular Human Motion Capture (2019)
  • Realtime 3D Human Pose Estimation (2019)
  • Texturesynthesis using Generative Adversarial Networks (2019)
  • Dimensionsreduktionsmethoden zur Kodierung menschlicher Posen (2019)
  • Tiefenschätzung zur 3D Rekonstruktion menschlicher Posen (2019)
  • Roboterkinematikbasierte Registrierung eines Augmented Reality Systems (2019)