Prof. Dr. Vasileios Belagiannis
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Prof. Dr. Vasileios Belagiannis
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Our research focuses on basic and applied research in machine learning. We develop approaches for anomaly detection, uncertainty estimation, out-of-distribution detection, few-shot learning, noisy label learning, as well as hardware-aware algorithms for model compression and efficient design of neural network architectures. Our applications include medical image analysis with problems such as cell counting and segmentation in histology images, organ segmentation from CT and MRI volumes, and multi-label medical image segmentation.
Research projects
- Few-shot learning for medical images.
- Cell Segmentation.
- Multi-label image classification.
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ÖGP NXT GEN AI METHODS: Subcontracting within the framework of the ÖGP NXT GEN AI METHODS – Generative methods for perception, prediction, and planning (NXTAIM)
(Third Party Funds Single)
Project leader:
Term: 1. January 2026 - 31. December 2026
Acronym: ÖGP NXT GEN AI METHODS
Funding source: Industrie
URL: https://nxtaim.de/en/home/The aim of this project is to develop self-playing, multi-agent simulators based on GPUDrive. In this context, we will develop trajectory planning strategies with a focus on efficient training and optimisation. These strategies will then be tested in automated driving scenarios.
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BAVAR-RADAR: Bavarian Advanced Resolution Radar
(Third Party Funds Group – Sub project)
Overall project: Bavarian Advanced Resolution Radar
Project leader:
Term: 1. February 2025 - 31. January 2028
Acronym: BAVAR-RADAR
Funding source: Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie (StMWi) (seit 2018) -
SUSTAINET-inNOvAte: SUSTAINET-inNOvAte: Nachhaltige Technologien für fortschrittliche resiliente und energieeffiziente Netze - Reibungslose, sichere und widerstandsfähige Netze für die dynamische digitale Welt
(Third Party Funds Group – Sub project)
Overall project: Sustainable Technologies for Advanced Resilient and Energy-Efficient Networks - Frictionless, secure, and resilient communication networks for the dynamic digital world
Project leader:
Term: 1. January 2025 - 31. December 2027
Acronym: SUSTAINET-inNOvAte
Funding source: BMFTR / Verbundprojekt -
Unterbeauftragung ÖGP NXT-AIM: Subcontracting within the framework of the ÖGP NXT-AIM Generative Modeling
(Third Party Funds Single)
Project leader:
Term: 1. January 2024 - 31. December 2026
Acronym: Unterbeauftragung ÖGP NXT-AIM
Funding source: Industrie
URL: https://nxtaim.de/en/home/The project deals with two aspects of generative modeling. First, generative models, especially fundamental models, have made a significant contribution in the areas of image, text, and audio. However, they have not yet been well researched for sequential and unstructured data, such as automotive data. Second, the latent spatial representation in generative models is not interpretable. However, this is linked to the predicted or generated output. This project aims to explore generative models for trajectory planning by integrating robustness measures.
2026
- El-Ghoussani, A., Kaup, A., Navab, N., Carneiro, G., & Belagiannis, V. (2026). Visual Autoregressive Modelling for Monocular Depth Estimation. In Proceedings of the Proceedings of the 21st International Conference on Computer Vision Theory and Applications (pp. 44-54). Marbella, ES.
- Fröhlich, J., Heinlein, B., Claar, J., Rosenberger, H., Belagiannis, V., & Müller, R. (2026). The Confusion is Real: GRAPHIC - A Network Science Approach to Confusion Matrices in Deep Learning. Transactions on Machine Learning Research.
- Ritthaler, M., Hussian, A., Belagiannis, V., & Kaup, A. (2026). Point Cloud Upsampling through Patch-based Frequency Superposition. In Proceedings of the European Conference on Signal Processing (EUSIPCO). Bruges, BE.
2025
- Asthana, R., Conrad, J., Ortmanns, M., & Belagiannis, V. (2025). Dextr: Zero-Shot Neural Architecture Search with Singular Value Decomposition and Extrinsic Curvature. Transactions on Machine Learning Research, 2025-August. https://doi.org/10.48550/arXiv.2508.12977
- Conrad, J., Wilhelmstätter, S., Mandry, H., Kässer, P., Abdelaal, A., Asthana, R.,... Ortmanns, M. (2025). PSumSim: A Simulator for Partial-Sum Quantization in Analog Matrix-Vector Multipliers. In Proceedings - IEEE International Symposium on Circuits and Systems. London, GB: Institute of Electrical and Electronics Engineers Inc..
- De Vita, M., & Belagiannis, V. (2025). Diffusion Model Guided Sampling with Pixel-Wise Aleatoric Uncertainty Estimation. In Proceedings - 2025 IEEE Winter Conference on Applications of Computer Vision, WACV 2025 (pp. 3844-3854). Tucson, AZ, US: Institute of Electrical and Electronics Engineers Inc..
- Hoang, D.A., Nguyen, C., Belagiannis, V., Do, T.T., & Carneiro, G. (2025). Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning. Transactions on Machine Learning Research, 2025-March.
- Hofmann, B., Regenhardt, K., Bründl, P., Nguyen, H.G., Belagiannis, V., Franke, J., & Risch, F. (2025). Machine learning-based prediction of quality characteristics in joining processes to minimize destructive testing: A case study on crimp connections. Procedia CIRP, 134, 163-168. https://doi.org/10.1016/j.procir.2025.03.030
- Hornauer, J., El-Ghoussani, A., & Belagiannis, V. (2025). Revisiting Gradient-Based Uncertainty for Monocular Depth Estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/TPAMI.2025.3541964
- Hölle, M., Kellermann, W., & Belagiannis, V. (2025). Uncertainty-Aware Likelihood Ratio Estimation for Pixel-Wise Out-of-Distribution Detection. In IEEE/CVF (Eds.), Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops (pp. 772-782). Honolulu, HI, US.
- Liu, Y., Chen, Y., Wang, H., Belagiannis, V., Reid, I., & Carneiro, G. (2025). ItTakesTwo: Leveraging Peer Representations for Semi-supervised LiDAR Semantic Segmentation. In Aleš Leonardis, Elisa Ricci, Stefan Roth, Olga Russakovsky, Torsten Sattler, Gül Varol (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 81-99). Milan, IT: Springer Science and Business Media Deutschland GmbH.
2024
- Asthana, R., Conrad, J., Dawoud, Y., Ortmanns, M., & Belagiannis, V. (2024). Multi-conditioned Graph Diffusion for Neural Architecture Search. Transactions on Machine Learning Research.
- Conrad, J., Kauffman, J., Wilhelmstatter, S., Asthana, R., Belagiannis, V., & Ortmanns, M. (2024). Confidence Estimation and Boosting for Dynamic-Comparator Transient-Noise Analysis. In 2024 22nd IEEE Interregional NEWCAS Conference (NEWCAS) (pp. 1-5). Sherbrooke, QC, CA: Institute of Electrical and Electronics Engineers Inc..
- Conrad, J., Wilhelmstatter, S., Asthana, R., Belagiannis, V., & Ortmanns, M. (2024). Differentiable Cost Model for Neural-Network Accelerator Regarding Memory Hierarchy. IEEE Transactions on Circuits and Systems I-Regular Papers. https://doi.org/10.1109/TCSI.2024.3476534
- Conrad, J., Wilhelmstatter, S., Asthana, R., Belagiannis, V., & Ortmanns, M. (2024). Too-Hot-to-Handle: Insights into Temperature and Noise Hyperparameters for Differentiable Neural-Architecture-Searches. In 2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS) (pp. 557-561). Abu Dhabi, AE: Institute of Electrical and Electronics Engineers Inc..
- El-Ghoussani, A., Hornauer, J., Carneiro, G., & Belagiannis, V. (2024). Consistency Regularisation for Unsupervised Domain Adaptation in Monocular Depth Estimation. In Proceedings of the Third Conference on Lifelong Learning Agents (CoLLAs 2024). Polo Didattico San Rossore 1938 building of the University of Pisa, Italy.
- Liu, Y., Tian, Y., Wang, C., Chen, Y., Liu, F., Belagiannis, V., & Carneiro, G. (2024). Translation Consistent Semi-supervised Segmentation for 3D Medical Images. IEEE Transactions on Medical Imaging. https://doi.org/10.1109/TMI.2024.3468896
- Tsaregorodtsev, A., Buchholz, M., & Belagiannis, V. (2024). Infrastructure-based Perception with Cameras and Radars for Cooperative Driving Scenarios. In IEEE Intelligent Vehicles Symposium, Proceedings (pp. 1678-1685). Jeju Island, KR: Institute of Electrical and Electronics Engineers Inc..
2023
- Briegleb, A., Haubner, T., Belagiannis, V., & Kellermann, W. (2023). Localizing Spatial Information in Neural Spatiospectral Filters. In IEEE (Eds.), Proceedings of the 2023 31st European Signal Processing Conference (EUSIPCO) (pp. 920-924). Helsinki, Finland.
- Dawoud, Y., Bouazizi, A., Ernst, K., Carneiro, G., & Belagiannis, V. (2023). Knowing What to Label for Few Shot Microscopy Image Cell Segmentation. In Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023 (pp. 3557-3566). Waikoloa, HI, USA: Institute of Electrical and Electronics Engineers Inc..
- Dawoud, Y., Carneiro, G., & Belagiannis, V. (2023). SelectNAdapt: Support Set Selection for Few-Shot Domain Adaptation. In Proceedings - 2023 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2023 (pp. 973-982). Paris, FRA: Institute of Electrical and Electronics Engineers Inc..
- Holzbock, A., Hegde, A., Dietmayer, K., & Belagiannis, V. (2023). DATA-FREE BACKBONE FINE-TUNING FOR PRUNED NEURAL NETWORKS. In European Signal Processing Conference (pp. 1255-1259). Helsinki, FIN: European Signal Processing Conference, EUSIPCO.
- Holzbock, A., Tsaregorodtsev, A., & Belagiannis, V. (2023). Pedestrian Environment Model for Automated Driving. In IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC (pp. 534-540). Bilbao, ES: Institute of Electrical and Electronics Engineers Inc..
- Hornauer, J., & Belagiannis, V. (2023). Heatmap-based Out-of-Distribution Detection. In Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023 (pp. 2602-2611). Waikoloa, HI, USA: Institute of Electrical and Electronics Engineers Inc..
- Hornauer, J., Holzbock, A., & Belagiannis, V. (2023). Out-of-Distribution Detection for Monocular Depth Estimation. In Proceedings of the IEEE International Conference on Computer Vision (pp. 1911-1921). Paris, FR: Institute of Electrical and Electronics Engineers Inc..
- Liu, Y., Ding, C., Tian, Y., Pang, G., Belagiannis, V., Reid, I., & Carneiro, G. (2023). Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation. In 2023 IEEE/CVF International Conference on Computer Vision (ICCV) (pp. 1151-1161). Paris, FR: Institute of Electrical and Electronics Engineers Inc..
- Schmidt, J., Huissel, P., Wiederer, J., Jordan, J., Belagiannis, V., & Dietmayer, K. (2023). RESET: Revisiting Trajectory Sets for Conditional Behavior Prediction. In IEEE Intelligent Vehicles Symposium, Proceedings. Anchorage, AK, USA: Institute of Electrical and Electronics Engineers Inc..
- Tsaregorodtsev, A., & Belagiannis, V. (2023). ParticleAugment: Sampling-based data augmentation. Computer Vision and Image Understanding, 228. https://doi.org/10.1016/j.cviu.2023.103633
- Tsaregorodtsev, A., Buchholz, M., & Belagiannis, V. (2023). Automated Automotive Radar Calibration With Intelligent Vehicles. In European Signal Processing Conference (pp. 800-804). Helsinki, FIN: European Signal Processing Conference, EUSIPCO.
- Wiederer, J., Schmidt, J., Kressel, U., Dietmayer, K., & Belagiannis, V. (2023). Joint Out-of-Distribution Detection and Uncertainty Estimation for Trajectory Prediction. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 5487-5494). Detroit, MI, US: Institute of Electrical and Electronics Engineers Inc..
2022
- Kern, N., Holzbock, A., Grebner, T., Belagiannis, V., Dietmayer, K., & Waldschmidt, C. (2022). A Ground Truth System for Radar Measurements of Humans. In 2022 German Microwave Conference, GeMiC 2022 (pp. 84-87). Ulm, DEU: Institute of Electrical and Electronics Engineers Inc..
- Ülger, O., Wiederer, J., Ghafoorian, M., Belagiannis, V., & Mettes, P. (2022). Multi-Task Edge Prediction in Temporally-Dynamic Video Graphs. In BMVC 2022 - 33rd British Machine Vision Conference Proceedings. London, GBR: British Machine Vision Association, BMVA.
2021
- Bouazizi, A., Kressel, U., & Belagiannis, V. (2021). Learning Temporal 3D Human Pose Estimation with Pseudo-Labels. In AVSS 2021 - 17th IEEE International Conference on Advanced Video and Signal-Based Surveillance. Virtual, Online, USA: Institute of Electrical and Electronics Engineers Inc..
- Bouazizi, A., Wiederer, J., Kressel, U., & Belagiannis, V. (2021). Self-Supervised 3D Human Pose Estimation with Multiple-View Geometry. In Vitomir Struc, Marija Ivanovska (Eds.), Proceedings - 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2021. Virtual, Jodhpur, IND: Institute of Electrical and Electronics Engineers Inc..
- Casas, L., Klimmek, A., Navab, N., & Belagiannis, V. (2021). Adversarial signal denoising with encoder-decoder networks. In European Signal Processing Conference (pp. 1467-1471). Amsterdam, NLD: European Signal Processing Conference, EUSIPCO.
- Conrad, J., Jiang, B., Kaesser, P., Ortmanns, M., & Belagiannis, V. (2021). Nonlinearity Modeling for Mixed-Signal Inference Accelerators in Training Frameworks. In 2021 28th IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2021 - Proceedings. Dubai, ARE: Institute of Electrical and Electronics Engineers Inc..
- Dawoud, Y., Hornauer, J., Carneiro, G., & Belagiannis, V. (2021). Few-Shot Microscopy Image Cell Segmentation. In Yuxiao Dong, Dunja Mladenic, Craig Saunders (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 139-154). Virtual, Online: Springer Science and Business Media Deutschland GmbH.
- Engel, N., Belagiannis, V., & Dietmayer, K. (2021). Attention-based Vehicle Self-Localization with HD Feature Maps. In IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC (pp. 76-83). Indianapolis, IN, USA: Institute of Electrical and Electronics Engineers Inc..
- Engel, N., Dietmayer, K., & Belagiannis, V. (2021). Point transformer. IEEE Access, 9, 134826-134840. https://doi.org/10.1109/ACCESS.2021.3116304
- Hasan, I., Setti, F., Tsesmelis, T., Amin, S., Del Bue, A., Cristani, M.,... Belagiannis, V. (2021). Forecasting People Trajectories and Head Poses by Jointly Reasoning on Tracklets and Vislets. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(4), 1267-1278. https://doi.org/10.1109/TPAMI.2019.2949414
- Hornauer, J., Nalpantidis, L., & Belagiannis, V. (2021). Visual Domain Adaptation for Monocular Depth Estimation on Resource-Constrained Hardware. In Proceedings of the IEEE International Conference on Computer Vision (pp. 954-962). Virtual, Online, CAN: Institute of Electrical and Electronics Engineers Inc..
- Liu, F., Tian, Y., Cordeiro, F.R., Belagiannis, V., Reid, I., & Carneiro, G. (2021). Self-supervised Mean Teacher for Semi-supervised Chest X-Ray Classification. In Chunfeng Lian, Xiaohuan Cao, Islem Rekik, Xuanang Xu, Pingkun Yan (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 426-436). Virtual: Springer Science and Business Media Deutschland GmbH.
- Sachdeva, R., Cordeiro, F.R., Reid, I., Carneiro, G., & Belagiannis, V. (2021). EvidentialMix: Learning with combined open-set and closed-set noisy labels. In Proceedings - 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021 (pp. 3606-3614). Virtual, US: Institute of Electrical and Electronics Engineers Inc..
- Schreiber, M., Glaeser, C., Dietmayer, K., & Belagiannis, V. (2021). Dynamic Occupancy Grid Mapping with Recurrent Neural Networks. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 6717-6724). Xi'an, CHN: Institute of Electrical and Electronics Engineers Inc..
2020
- Horn, M., Engel, N., Belagiannis, V., Buchholz, M., & Dietmayer, K. (2020). DeepCLR: Correspondence-Less Architecture for Deep End-to-End Point Cloud Registration. In 2020 IEEE 23rd International Conference on Intelligent Transportation Systems, ITSC 2020. Rhodes, GRC: Institute of Electrical and Electronics Engineers Inc..
- Schreiber, M., Belagiannis, V., Glaser, C., & Dietmayer, K. (2020). Motion Estimation in Occupancy Grid Maps in Stationary Settings Using Recurrent Neural Networks. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 8587-8593). Paris, FRA: Institute of Electrical and Electronics Engineers Inc..
- Strohbeck, J., Mueller, J., Schreiber, M., Herrmann, M., Wolf, D., Buchholz, M., & Belagiannis, V. (2020). Multiple trajectory prediction with deep temporal and spatial convolutional neural networks. In IEEE International Conference on Intelligent Robots and Systems (pp. 1992-1998). Las Vegas, NV, USA: Institute of Electrical and Electronics Engineers Inc..
- Teich, W.G., Liu, R., & Belagiannis, V. (2020). Deep Learning versus High-order Recurrent Neural Network based Decoding for Convolutional Codes. In 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings. Virtual, Taipei, TWN: Institute of Electrical and Electronics Engineers Inc..
- Wiederer, J., Bouazizi, A., Kressel, U., & Belagiannis, V. (2020). Traffic control gesture recognition for autonomous vehicles. In IEEE International Conference on Intelligent Robots and Systems (pp. 10676-10683). Las Vegas, NV, USA: Institute of Electrical and Electronics Engineers Inc..