HighScene – Online Scenarios from Highway Infrastructure

The goal of High-Scene is to generate valuable information out of the huge amount of data that is available in the more than 9000 Highway cameras in Austria. The project investigates novel and innovative on-line learning algorithms for vehicle detection and tracking to improve the localization performance, especially in difficult weather and illumination conditions. Vehicle trajectories will be clustered and analyzed to identify outliers on the one hand, e.g. dangerous traffic situations.

Dissemination

MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection J. Micorek, H. Possegger, D. Narnhofer, H. Bischof, M. Koziński In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

ActMAD: Activation Matching to Align Distributions for Test-Time-Training M. J. Mirza, P. J. Soneira, W. Lin, M. Kozinski, H. Possegger, H. Bischof In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.

Towards Large-Scale Video-Based Highway Traffic Monitoring J. Spoecklberger, J. Micorek, H. Possegger, H. Bischof In Proc. of the IEEE International Conference on Intelligent Transportation Systems (ITSC), 2023.

MATE: Masked Autoencoders are Online 3D Test-Time Learner M. J. Mirza, I. Shin, W. Lin, A. Schriebl, K. Sun, J. Choe, M. Kozinski, H. Possegger, I. S. Kweon, K. Yoon, H. Bischof In Proc. of the International Conference on Computer Vision (ICCV), 2023.

Sit Back and Relax: Learning to Drive Incrementally in All Weather Conditions S. Leitner, M. J. Mirza, W. Lin, J. Micorek, M. Masana, M. Kozinski, H. Possegger, H. Bischof In Proc. of the IEEE Intelligent Vehicles Symposium (IV), 2023.

The Norm Must Go On: Dynamic Unsupervised Domain Adaptation by Normalization M. J. Mirza, J. Micorek, H. Possegger, H. Bischof In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.

An Efficient Domain-Incremental Learning Approach to Drive in All Weather Condition M. J. Mirza, M. Masana, H. Possegger, H. Bischof In Proc. of the Vision for all Seasons: Adverse Weather and Lighting Conditions Workshop (V4AS, CVPR Workshop), 2022.

Project Funding

This project received funding from the Mobility of the Future programme under the project High-Scene (884306). Mobility of the Future is a research, technology and innovation funding programme of the Republic of Austria, Ministry for Climate Action. The Austrian Research Promotion Agency (FFG) has been authorised for the programme management.

HighScene – Online Scenarios from Highway Infrastructure

Project Consortium

Project Duration

Dissemination

Project Funding