Vasileios Belagiannis

Prof. Dr. Vasileios Belagiannis

Professorship for Machine Learning in Signal Processing

Department of Electrical-Electronic-Communication Engineering
Chair of Multimedia Communications and Signal Processing

Room: Room 06.033
Cauerstr. 7
91058 Erlangen

Office hours

By arrangement.

Vasileios Belagiannis is Professor at the Faculty of Engineering of the Friedrich-Alexander-Universität Erlangen-Nürnberg. He holds a degree in engineering (Greece, 2009) from Democritus University of Thrace, Engineering School of Xanthi and M.Sc. in Computational Science and Engineering from TU München (Germany, 2011). He completed his doctoral studies at TU München (2015) and then continued as post-doctoral research assistant at the University of Oxford (Visual Geometry Group). Prior to joining Friedrich-Alexander-Universität Erlangen-Nürnberg, he spent time in industry, working at OSRAM, and then Ulm University and Otto von Guericke University Magdeburg.

An updated list of publications can be found on Google Scholar.

I am always looking for highly motivated students to undertake a PhD.

Recent News:

Prof. Belagiannis leads the Machine Learning & Perception (MLP) group. The MLP group focuses on machine learning, particularly deep learning, for both fundamental and applied research. Current research includes generative models, anomaly detection, uncertainty estimation, out-of-distribution detection, few-shot learning, noisy label learning, and hardware-aware machine learning such as model compression and neural architecture search. Applications range from automated driving, computer vision and medical image analysis to signal processing and robotics.

 

Amir El-Ghoussani, M.Sc.

Room: Room 02.026

Arij Bouazizi, M.Sc.

Marc Hölle, M.Sc.

Room: Room 06.018

Julian Wiederer, M.Sc.

Michele De Vita, M.Sc.

Room: Room 02.026

Rohan Asthana, M.Sc.

Room: Room 02.026

Youssef Dawoud, M.Sc.

2024

2023

2022

2021

2020

2019

2018

2017

  • , :
    Recurrent Human Pose Estimation
    12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017 (Washington, DC, 30. May 2017 - 3. June 2017)
    In: Proceedings - 12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017 - 1st International Workshop on Adaptive Shot Learning for Gesture Understanding and Production, ASL4GUP 2017, Biometrics in the Wild, Bwild 2017, Heterogeneous Face Recognition, HFR 2017, Joint Challenge on Dominant and Complementary Emotion Recognition Using Micro Emotion Features and Head-Pose Estimation, DCER and HPE 2017 and 3rd Facial Expression Recognition and Analysis Challenge, FERA 2017
    DOI: 10.1109/FG.2017.64
    BibTeX: Download
  • , , , , , , , :
    Preface DLMIA 2017
    In: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support - 3rd International Workshop, DLMIA 2017 and 7th International Workshop, ML-CDS 2017 Held in Conjunction with MICCAI 2017, Proceedings, Springer Verlag, (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol.10553 LNCS)
    BibTeX: Download

2016

2015

2014

2012

2009

  • , , , , , :
    The vision system of the ACROBOTER project
    2nd International Conference on Intelligent Robotics and Applications, ICIRA 2009 (SGP, 16. December 2009 - 18. December 2009)
    In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    DOI: 10.1007/978-3-642-10817-4_94
    BibTeX: Download

  • Always-on Deep Neural Networks

    (Third Party Funds Single)

    Term: 1. March 2023 - 28. February 2026
    Funding source: DFG-Einzelförderung / Sachbeihilfe (EIN-SBH)
    Abstract
    Computer vision contributes in creating visual priors as self-contained tasks or input to another system. In the context of autonomous navigation, the system can be a mobile agent that not only relies on the raw sensory inputs, but also on computer vision algorithms for understanding the environment. Recent studies on embodied agents show that an agent acts more accurately when visual priors such as semantic segmentation, depth estimation are provided next to the raw input data. Producing the visual priors though comes at the cost of data collection and annotation. The latest approaches build on deep neural networks, which are trained with supervision. For that propose, a large pool of data and annotations has to be created prior to training the model. To address this limitation, simulation is an alternative source for data and annotation generation. In the context of deep neural networks, it can be considered for the replacing the real-world, where a large amount of synthetic data is created according to the task in place. Although, the data simulation has clear advantages over the real-world datasets, there is also a clear limitation. Training a deep neural network with synthetic data does not result in good performance on real-world data.In this research project, we are going to conduct research on closing the performance drop when transferring deep neural network models from the simulation to real-world applications. Our testbed for measuring the performance will be semantic image segmentation and depth estimation from a single image. In our research, we will propose algorithms that teach a deep neural network how to fast learn adapting into new environments. This concept is widely known as meta-learning. In this project, it will be explored for learning a model in simulation and then transferring it to the real-world. Meta-learning has never been seen as a way to tackle model transfer, but its formulation suits well to the problem.

  • Transfer von tiefen neuronalen Netzen von der Simulation in die reale Welt

    (Third Party Funds Single)

    Term: 1. December 2022 - 30. November 2025
    Funding source: DFG-Einzelförderung / Sachbeihilfe (EIN-SBH)
    Abstract

    Computer vision contributes in creating visual priors as self-contained tasks or input to another system. In the context of autonomous navigation, the system can be a mobile agent that not only relies on the raw sensory inputs, but also on computer vision algorithms for understanding the environment. Recent studies on embodied agents show that an agent acts more accurately when visual priors such as semantic segmentation, depth estimation are provided next to the raw input data. Producing the visual priors though comes at the cost of data collection and annotation. The latest approaches build on deep neural networks, which are trained with supervision. For that propose, a large pool of data and annotations has to be created prior to training the model. To address this limitation, simulation is an alternative source for data and annotation generation. In the context of deep neural networks, it can be considered for the replacing the real-world, where a large amount of synthetic data is created according to the task in place. Although, the data simulation has clear advantages over the real-world datasets, there is also a clear limitation. Training a deep neural network with synthetic data does not result in good performance on real-world data.In this research project, we are going to conduct research on closing the performance drop when transferring deep neural network models from the simulation to real-world applications. Our testbed for measuring the performance will be semantic image segmentation and depth estimation from a single image. In our research, we will propose algorithms that teach a deep neural network how to fast learn adapting into new environments. This concept is widely known as meta-learning. In this project, it will be explored for learning a model in simulation and then transferring it to the real-world. Meta-learning has never been seen as a way to tackle model transfer, but its formulation suits well to the problem.

Lectures

  • Machine Learning in Signal Processing
    • Further information is available on StudOn and Campo.
  • Introduction to Deep Learning
    • Further information is available on StudOn and Campo.
  • Advanced Topics in Deep Learning
    • Further information is available on StudOn and Campo.
  • Perception in Robotics
    • Further information is available on StudOn and Campo.

Guide to scientific work

  • Guide to scientific work
    • Further information is available on StudOn and Campo.

Seminars

  • Seminar on Selected Topics in Machine Learning
    • Further information is available on StudOn and Campo.
  • Seminar on Selected Topics in Multimedia Communications and Signal Processing
    • Further information is available on StudOn and Campo.
  • Seminar on Selected Topics in Machine Learning
    • Further information is available on StudOn and Campo.
  • Seminar über Bachelor- und Masterarbeiten
    • Further information is available on StudOn and Campo.

Lab Courses

  • Machine Learning in Signal Processing
    • Further information is available on StudOn and Campo.
Adrian Holzbock, Alexander Tsaregorodtsev, Vasileios Belagiannis
Pedestrian Environment Model for Automated Driving

Julian Wiederer, Julian Schmidt, Ulrich Kressel, Klaus Dietmayer, Vasileios Belagiannis

Joint Out-of-Distribution Detection and Uncertainty Estimation for Trajectory Prediction

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Alexander Tsaregorodtsev, Michael Buchholz, Vasileios Belagiannis
Automated Automotive Radar Calibration With Intelligent Vehicles

Adrian Holzbock, Achyut Hegde, Klaus Dietmayer, Vasileios Belagiannis

Data-Free Backbone Fine-Tuning for Pruned Neural Networks

Alexander Tsaregorodtsev, Adrian Holzbock, Jan Strohbeck, Michael Buchholz, Vasileios Belagiannis

Automated Static Camera Calibration with
Intelligent Vehicles

Julian Schmidt, Pascal Huissel, Julian Wiederer, Julian Jordan, Vasileios Belagiannis, Klaus Dietmayer
RESET: Revisiting Trajectory Sets for Conditional Behavior Prediction

Annika Briegleb, Thomas Haubner, Vasileios Belagiannis, Walter Kellermann
Localizing Spatial Information in Neural Spatiospectral Filters

Alexander Tsaregorodtsev, Vasileios Belagiannis, ParticleAugment: Sampling-based data augmentation, Computer Vision and Image Understanding, 2023.

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Ragav Sachdeva, Filipe Rolim Cordeiro, Vasileios Belagiannis, Ian Reid, Gustavo Carneiro, ScanMix: Learning from Severe Label Noise via Semantic Clustering and Semi-Supervised Learning, Pattern Recognition, 2023.

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Dawoud, Youssef, Bouazizi, Arij, Ernst, Katharina, Carneiro, Gustavo, Belagiannis, Vasileios, Knowing What To Label for Few Shot Microscopy Image Cell Segmentation, Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023.

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Hornauer, Julia, Belagiannis, Vasileios, Heatmap-Based Out-of-Distribution Detection, Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023.

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Cuong C. Nguyen, Youssef Dawoud, Thanh-Toan Do, Jacinto C. Nascimento, Vasileios Belagiannis, Gustavo Carneiro, Smart task design for meta learning medical image analysis systems: Unsupervised, weakly-supervised, and cross-domain design of meta learning tasks, Meta Learning With Medical Imaging and Health Informatics Applications, 2023.

Publication

Filipe R. Cordeiro, Ragav Sachdeva, Vasileios Belagiannis, Ian Reid, Gustavo Carneiro, LongReMix: Robust learning with high confidence samples in a noisy label environment, Pattern Recognition, 2023.

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Ülger, Osman, Wiederer, Julian, Ghafoorian, Mohsen, Belagiannis, Vasileios, Mettes, Pascal, Multi-Task Edge Prediction in Temporally-Dynamic Video Graphs, 33rd British Machine Vision Conference 2022, {BMVC} 2022, 2022.

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Holzbock, Adrian, Kern, Nicolai, Waldschmidt, Christian, Dietmayer, Klaus, Belagiannis, Vasileios, Gesture Recognition with Keypoint and Radar Stream Fusion for Automated Vehicles, Computer Vision – {ECCV} 2022 Workshops, 2022.

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Hornauer, Julia, Belagiannis, Vasileios, Gradient-based uncertainty for monocular depth estimation, European Conference on Computer Vision, 2022.

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Wiederer, Julian, Schmidt, Julian, Kressel, Ulrich, Dietmayer, Klaus, Belagiannis, Vasileios, A benchmark for unsupervised anomaly detection in multi-agent trajectories, 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 2022.

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Tsaregorodtsev, Alexander, Muller, Johannes, Strohbeck, Jan, Herrmann, Martin, Buchholz, Michael, Belagiannis, Vasileios, Extrinsic camera calibration with semantic segmentation, 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 2022.

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Liu, Fengbei, Chen, Yuanhong, Tian, Yu, Liu, Yuyuan, Wang, Chong, Belagiannis, Vasileios, Carneiro, Gustavo, NVUM: Non-volatile Unbiased Memory for Robust Medical Image Classification, International Conference on Medical Image Computing and Computer-Assisted Intervention, 2022.

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Dawoud, Youssef, Ernst, Katharina, Carneiro, Gustavo, Belagiannis, Vasileios, Edge-based self-supervision for semi-supervised few-shot microscopy image cell segmentation, International Workshop on Medical Optical Imaging and Virtual Microscopy Image Analysis, 2022.

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Bouazizi, Arij, Holzbock, Adrian, Kressel, Ulrich, Dietmayer, Klaus, Belagiannis, Vasileios, Motionmixer: Mlp-based 3d human body pose forecasting, Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, {IJCAI} 2022, 2022.

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Holzbock, Adrian, Tsaregorodtsev, Alexander, Dawoud, Youssef, Dietmayer, Klaus, Belagiannis, Vasileios, A spatio-temporal multilayer perceptron for gesture recognition, 2022 IEEE Intelligent Vehicles Symposium (IV), 2022.

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Rudolph, Michael, Dawoud, Youssef, Güldenring, Ronja, Nalpantidis, Lazaros, Belagiannis, Vasileios, Lightweight monocular depth estimation through guided decoding, 2022 International Conference on Robotics and Automation (ICRA), 2022.

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Liu, Yuyuan, Tian, Yu, Chen, Yuanhong, Liu, Fengbei, Belagiannis, Vasileios, Carneiro, Gustavo, Perturbed and strict mean teachers for semi-supervised semantic segmentation, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022.

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Liu, Fengbei, Tian, Yu, Chen, Yuanhong, Liu, Yuyuan, Belagiannis, Vasileios, Carneiro, Gustavo, ACPL: Anti-curriculum pseudo-labelling for semi-supervised medical image classification, Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2022.

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Schreiber, Marcel, Belagiannis, Vasileios, Gläser, Claudius, Dietmayer, Klaus, A multi-task recurrent neural network for end-to-end dynamic occupancy grid mapping, 2022 IEEE Intelligent Vehicles Symposium (IV), 2022.

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Conrad, Joschua, Jiang, Biyi, Kässer, Paul, Belagiannis, Vasileios, Ortmanns, Maurits, Nonlinearity Modeling for Mixed-Signal Inference Accelerators in Training Frameworks, 2021 28th IEEE International Conference on Electronics, Circuits, and Systems (ICECS), 2021.

Publication
Cordeiro, F. R., Belagiannis, Vasileios, Reid, Ian, Carneiro, Gustavo, PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels, The 32nd British Machine Vision Conference, 2021.

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Bouazizi, Arij, Kressel, Ulrich, Belagiannis, Vasileios, Learning Temporal 3D Human Pose Estimation with Pseudo-Labels, 2021 17th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2021.

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Engel, Nico, Belagiannis, Vasileios, Dietmayer, Klaus, Point Transformer, IEEE Access, 2021.

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Liu, Fengbei, Tian, Yu, Cordeiro, Filipe R, Belagiannis, Vasileios, Reid, Ian, Carneiro, Gustavo, Self-supervised mean teacher for semi-supervised chest x-ray classification, International Workshop on Machine Learning in Medical Imaging, 2021.

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Wiederer, Julian, Bouazizi, Arij, Troina, Marco, Kressel, Ulrich, Belagiannis, Vasileios, Anomaly Detection in Multi-Agent Trajectories for Automated Driving, Conference on Robot Learning, 2022.

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Kern, Nicolai, Holzbock, Adrian, Grebner, Timo, Belagiannis, Vasileios, Dietmayer, Klaus, Waldschmidt, Christian, A ground truth system for radar measurements of humans, 2022 14th German Microwave Conference (GeMiC), 2022.

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Farshad, Azade, Makarevich, Anastasia, Belagiannis, Vasileios, Navab, Nassir, MetaMedSeg: Volumetric Meta-learning for Few-Shot Organ Segmentation, MICCAI Workshop on Domain Adaptation and Representation Transfer, 2022.

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Hornauer, Julia, Nalpantidis, Lazaros, Belagiannis, Vasileios, Visual Domain Adaptation for Monocular Depth Estimation on Resource-Constrained Hardware, Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021.

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Bouazizi, Arij, Wiederer, Julian, Kressel, Ulrich, Belagiannis, Vasileios, Self-supervised 3d human pose estimation with multiple-view geometry, 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021), 2021.

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Engel, Nico, Belagiannis, Vasileios, Dietmayer, Klaus, Attention-based Vehicle Self-Localization with HD Feature Maps, 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021.

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Schreiber, Marcel, Belagiannis, Vasileios, Gläser, Claudius, Dietmayer, Klaus, Dynamic Occupancy Grid Mapping with Recurrent Neural Networks, 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021.

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Sachdeva, Ragav, Cordeiro, Filipe R, Belagiannis, Vasileios, Reid, Ian, Carneiro, Gustavo, EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels, Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2021.

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Werner Teich,Ruiqi Liu,Vasileios Belagiannis, Deep Learning versus High-order Recurrent Neural Network based Decoding for Convolutional Codes, GLOBECOM 2020 – 2020 IEEE Global Communications Conference, 2020.
Youssef Dawoud,Julia Hornauer,Gustavo Carneiro,Vasileios Belagiannis, Few-Shot Microscopy Image Cell Segmentation, Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2020.
Leslie Casas,Attila Klimmek,Nassir Navab,Vasileios Belagiannis, Adversarial Signal Denoising with Encoder-Decoder Networks, 2020 28th European Signal Processing Conference (EUSIPCO), 2021.
Wiederer, Julian, Bouazizi, Arij, Kressel, Ulrich, Belagiannis, Vasileios, Traffic Control Gesture Recognition for Autonomous Vehicles, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.
Strohbeck, Jan, Belagiannis, Vasileios, Müller, Johannes, Herrmann, Martin, Schreiber, Marcel, Buchholz, Michael, Multiple Trajectory Prediction with Deep Temporal and Spatial Convolutional Neural Networks, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.
Horn, Markus, Engel, Nico, Belagiannis, Vasileios, Buchholz, Michael, Dietmayer, Klaus, DeepCLR: Correspondence-Less Architecture for Deep End-to-End Point Cloud Registration, 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), 2020.
Schreiber, Marcel, Belagiannis, Vasileios, Gläser, Claudius, Dietmayer, Klaus, Motion Estimation in Occupancy Grid Maps in Stationary Settings Using Recurrent Neural Networks, 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020.
Nico Engel,Stefan Hoermann,Markus Horn,Vasileios Belagiannis,Klaus Dietmayer, DeepLocalization: Landmark-based Self-Localization with Deep Neural
Networks, 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019.
Johannes Müller,Martin Herrmann,Jan Strohbeck,Vasileios Belagiannis,Michael Buchholz, {LACI:} Low-effort Automatic Calibration of Infrastructure Sensors, 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019.
Irtiza Hasan,Francesco Setti,Theodore Tsesmelis,Vasileios Belagiannis,Sikandar Amin,Alessio Del Bue,Marco Cristani,Fabio Galasso, Forecasting People Trajectories and Head Poses by Jointly Reasoning on Tracklets and Vislets, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.
Felix Achilles,Federico Tombari,Vasileios Belagiannis,Anna Mira Loesch,Soheyl Noachtar,Nassir Navab, Convolutional neural networks for real-time epileptic seizure detection, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2018.
Vasileios Belagiannis,Azade Farshad,Fabio Galasso, Adversarial Network Compression, Computer Vision – {ECCV} 2018 Workshops – Munich, Germany, September 8-14, 2018, Proceedings, Part {IV}, 2018.
Vasileios Belagiannis,Andrew Zisserman, Recurrent Human Pose Estimation, 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), 2017.
Christoph Baur,Fausto Milletari,Vasileios Belagiannis,Nassir Navab,Pascal Fallavollita, Automatic 3D reconstruction of electrophysiology catheters from two-view monoplane C-arm image sequences, International journal of computer assisted radiology and surgery, 2016.
Nicola Rieke,David Joseph Tan,Chiara Amat di San Filippo,Federico Tombari,Mohamed Alsheakhali,Vasileios Belagiannis,Abouzar Eslami,Nassir Navab, Real-time localization of articulated surgical instruments in retinal microsurgery, Medical Image Analysis, 2016.
Vasileios Belagiannis,Xinchao Wang,Horesh Ben Shitrit,Kiyoshi Hashimoto,Ralf Stauder,Yoshimitsu Aoki,Michael Kranzfelder,Armin Schneider,Pascal Fua,Slobodan Ilic,Hubertus Feussner,Nassir Navab, Parsing human skeletons in an operating room, Machine Vision and Applications, 2016.
Vasileios Belagiannis,Sikandar Amin,Mykhaylo Andriluka,Bernt Schiele,Nassir Navab,Slobodan Ilic, 3D Pictorial Structures Revisited: Multiple Human Pose Estimation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016.
Shadi Albarqouni,Christoph Baur,Felix Achilles,Vasileios Belagiannis,Stefanie Demirci,Nassir Navab, AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images, IEEE transactions on medical imaging, 2016.
Iro Laina, Christian Rupprecht,Vasileios Belagiannis,Federico Tombari,Nassir Navab, Deeper Depth Prediction with Fully Convolutional Residual Networks, 2016 Fourth international conference on 3D vision (3DV), 2016.
Vasileios Belagiannis,Christian Rupprecht,Gustavo Carneiro,Nassir Navab, Robust Optimization for Deep Regression, Proceedings of the IEEE international conference on computer vision, 2015.
Falk Schubert,Daniele Casaburo,Dirk Dickmanns,Vasileios Belagiannis, Revisiting Robust Visual Tracking Using Pixel-Wise Posteriors, International Conference on Computer Vision Systems, 2015.
Nissler, Christian, Mouriki, Nikoleta, Castellini, Claudio, Belagiannis, Vasileios, Navab, Nassir, OMG: introducing optical myography as a new human machine interface for hand amputees, 2015 IEEE International Conference on Rehabilitation Robotics (ICORR), 2015.
Achilles, Felix, Belagiannis, Vasileios, Tombari, Federico, Loesch, Anna Mira, Cunha, Joao Paulo, Navab, Nassir, Noachtar, Soheyl, Deep convolutional neural networks for automatic identification of epileptic seizures in infrared and depth images, Journal of the Neurological Sciences, 2015.
Mehmet Yigitsoy,Vasileios Belagiannis,A. Djurka,Amin Katouzian,Slobodan Ilic,E. Pernus,Abouzar Eslami,Nassir Navab, Random ferns for multiple target tracking in microscopic retina image sequences, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015.
Lichao Wang,Vasileios Belagiannis,Carsten Marr,Fabian J. Theis,Guang{-}Zhong Yang,Nassir Navab, Anatomic-landmark detection using graphical context modelling, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015.
Nicola Rieke,David Joseph Tan,Mohamed Alsheakhali,Federico Tombari,Chiara Amat di San Filippo,Vasileios Belagiannis,Abouzar Eslami,Nassir Navab, Surgical Tool Tracking and Pose Estimation in Retinal Microsurgery, International Conference on Medical Image Computing and Computer-Assisted Intervention, 2015.
Vasileios Belagiannis,Christian Amann,Nassir Navab,Slobodan Ilic, Holistic Human Pose Estimation with Regression Forests, International Conference on Articulated Motion and Deformable Objects, 2014.
Vasileios Belagiannis,Sikandar Amin,Mykhaylo Andriluka,Bernt Schiele,Nassir Navab,Slobodan Ilic, 3D Pictorial Structures for Multiple Human Pose Estimation, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014.
Vasileios Belagiannis,Xinchao Wang,Bernt Schiele,Pascal Fua,Slobodan Ilic,Nassir Navab, Multiple Human Pose Estimation with Temporally Consistent 3D Pictorial
Structures, European Conference on Computer Vision Workshops, 2014.
Fausto Milletari,Vasileios Belagiannis,Nassir Navab,Pascal Fallavollita, Fully Automatic Catheter Localization in C-Arm Images Using L1-Sparse Coding, International Conference on Medical Image Computing and Computer-Assisted Intervention, 2014.
Vasileios Belagiannis,Falk Schubert,Nassir Navab,Slobodan Ilic, Segmentation Based Particle Filtering for Real-Time 2D Object Tracking, European Conference on Computer Vision, 2012.
Stauder, Ralf, Belagiannis, Vasileios, Schwarz, Loren, Bigdelou, Ali, Soehngen, Eric, Ilic, Slobodan, Navab, Nassir, A user-centered and workflow-aware unified display for the operating room, MICCAI Workshop on Modeling and Monitoring of Computer Assisted Interventions (M2CAI), 2012.
Rigas Kouskouridas,Nikolaos Kyriakoulis,Dimitrios Chrysostomou,Vasileios Belagiannis,Spyridon G. Mouroutsos,Antonios Gasteratos, The Vision System of the {ACROBOTER} Project, International Conference on Intelligent Robotics and Applications, 2009.
Kouskouridas, Rigas, Belagiannis, Vasileios, Gasteratos, Antonios, Kyriakoulis, Nikolaos, Chrysostomou, Dimitrios, Iosifidis, Alexandros, Karakasis, Evaggelos, Badekas,Efthimios, Mouroutsos, Spyridon G, Intelligent integrated vision system for indoor robotics applications, 5th, 2009.
Belagiannis, Vasileios, Gasteratos, Antonios, A real-time visual detection and tracking system, 3rd Pan-Hellenic Student Conference in Informatics, 2009.

Tsaregorodtsev, Alexander, Buchholz, Michael, Belagiannis, Vasileios, Automated Automotive Radar Calibration With Intelligent Vehicles, arXiv preprint arXiv:2306.13323, 2023.

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Holzbock, Adrian, Hegde, Achyut, Dietmayer, Klaus, Belagiannis, Vasileios, Data-Free Backbone Fine-Tuning for Pruned Neural Networks, arXiv preprint arXiv:2306.12881, 2023.

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Tsaregorodtsev, Alexander, Holzbock, Adrian, Strohbeck, Jan, Buchholz, Michael, Belagiannis, Vasileios, Automated Static Camera Calibration with Intelligent Vehicles, arXiv preprint arXiv:2304.10814, 2023.

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Schmidt, Julian, Huissel, Pascal, Wiederer, Julian, Jordan, Julian, Belagiannis, Vasileios, Dietmayer, Klaus, RESET: Revisiting Trajectory Sets for Conditional Behavior Prediction, arXiv preprint arXiv:2304.05856, 2023.

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Briegleb, Annika, Haubner, Thomas, Belagiannis, Vasileios, Kellermann, Walter, Localizing Spatial Information in Neural Spatiospectral Filters, arXiv preprint arXiv:2303.08052, 2023.

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Liu, Yuyuan, Ding, Choubo, Tian, Yu, Pang, Guansong, Belagiannis, Vasileios, Reid, Ian, Carneiro, Gustavo, Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation, arXiv preprint arXiv:2211.14512, 2022.

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