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Reviving Unsupervised Optical Flow: Concept Reevaluation, Multi-Scale Advances and Full Open-Source Release

A. Jahedi, M. Rivinius, N. Berenguel Senn, and A. Bruhn. 2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), page 1533-1542. (March 2026)

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Univ. -Prof. Dr. -Ing. Andrés Bruhn University of Stuttgart

PARC : A Quantitative Framework Uncovering the Symmetries within Vision Language ModelsJ. Schmalfuß, N. Chang, V. VS, M. Shen, A. Bruhn, and J. Alvarez. 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), page 25081-25091. IEEE, (2025)

Hon. -Prof. Ulrich Bruhnke University of Stuttgart

Andres Javier Zeller University of Stuttgart

Fabian Andres Tapias Hernandez University of Stuttgart

Javier Andres Carrillo Delcorto University of Stuttgart

Other publications of authors with the same name

Efficient Algorithms for Global Optimisation Methods in Computer Vision (Dagstuhl Seminar 11471).A. Bruhn, T. Pock, and X. Tai. Dagstuhl Reports, 1 (11): 66-90 (2011)Adaptive Integration of Feature Matches into Variational Optical Flow Methods.M. Stoll, S. Volz, and A. Bruhn. ACCV (3), volume 7726 of Lecture Notes in Computer Science, page 1-14. Springer, (2012)Multi-Scale Raft : Combining Hierarchical Concepts for Learning-Based Optical Flow EstimationA. Jahedi, L. Mehl, M. Rivinius, and A. Bruhn. 2022 IEEE International Conference on Image Processing (ICIP), page 1236-1240. IEEE, (2023)Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and StereoL. Mehl, J. Schmalfuss, A. Jahedi, Y. Nalivayko, and A. Bruhn. Dataset, (2023)Related to: Lukas Mehl, Jenny Schmalfuss, Azin Jahedi, Yaroslava Nalivayko, Andrés Bruhn: Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo. Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023. arXiv: 2303.01943.Vision for autonomous vehicles and probesA. Bruhn, A. Imiya, A. Leonardis, and T. Pajdla. 5, 11, page 36-61. Wadern, Schloss Dagstuhl, (2015)Variationsansätze zur Bewegungsschätzung: Präzise Modellierung und Effiziente Numerik.A. Bruhn. Ausgezeichnete Informatikdissertationen, volume D-7 of LNI, GI, (2006)M-FUSE : Multi-frame Fusion for Scene Flow EstimationL. Mehl, A. Jahedi, J. Schmalfuß, and A. Bruhn. 2023 IEEE Winter Conference on Applications of Computer Vision, page 2019-2028. Piscataway, NJ, IEEE, (2023)Subjective annotation for a frame interpolation benchmark using artefact amplificationH. Men, V. Hosu, H. Lin, A. Bruhn, and D. Saupe. Quality and User Experience, (2020)Article Number: 8.Order-adaptive and Illumination-aware Variational Optical Flow RefinementD. Maurer, A. Bruhn, and M. Stoll. Proceedings of the British Machine Vision Conference (BMVC), page 150:1-150:13. BMVA Press, (2017)Structure-from-motion-aware PatchMatch for Adaptive Optical Flow EstimationD. Maurer, N. Marniok, B. Goldluecke, and A. Bruhn. 11212, page 575-592. Springer International Publishing, (2018)