About
Simon Korman is a Senior Lecturer in the Department of Computer Science at the University of Haifa. His research is in computer vision and machine learning, with particular interest in learning and inference under limited, complex, or highly contaminated data.
Publications
- Unsupervised Representation Learning by Balanced Self Attention Matching, Shalam, D. & Korman, S., 2025, Computer Vision – ECCV 2024 - 18th European Conference, Proceedings. Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T. & Varol, G. (eds.). Springer Science and Business Media Deutschland GmbH, p. 269-285 17 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; vol. 15142 LNCS).
- Regularization for Unconditional Image Diffusion Models via Shifted Data Augmentation, Nakamura, K., Sohn, B. S., Korman, S. & Hong, B. W., 2025, In: IEEE Access. 13, p. 113258-113273 16 p.
- Generative adversarial networks via a composite annealing of noise and diffusion, Nakamura, K., Korman, S. & Hong, B. W., Feb 2024, In: Pattern Recognition. 146, 110034.
- The Balanced-Pairwise-Affinities Feature Transform, Shalam, D. & Korman, S., 2024, In: Proceedings of Machine Learning Research. 235, p. 44342-44357 16 p.
- SeaThru-NeRF: Neural Radiance Fields in Scattering Media, Levy, D., Peleg, A., Pearl, N., Rosenbaum, D., Akkaynak, D., Korman, S. & Treibitz, T., 2023, Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023. IEEE Computer Society, p. 56-65 10 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 2023-June).
- MFSC: Matching by Few-Shot Classification, Shalam, D., Abboud, E., Litman, R. & Korman, S., 2023.
- NAN: Noise-Aware NeRFs for Burst-Denoising, Pearl, N., Treibitz, T. & Korman, S., 2022, Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022. IEEE Computer Society, p. 12662-12671 10 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 2022-June).
- OATM: Occlusion Aware Template Matching by Consensus Set Maximization, Korman, S., Soatto, S. & Milam, M., 14 Dec 2018, Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018. IEEE Computer Society, p. 2675-2683 9 p. 8578381. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).
- Latent RANSAC, Korman, S. & Litman, R., 14 Dec 2018, Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018. IEEE Computer Society, p. 6693-6702 10 p. 8578798. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).
- Deleting and testing forbidden patterns in multi-dimensional arrays, Ben-Eliezer, O., Korman, S. & Reichman, D., 1 Jul 2017, 44th International Colloquium on Automata, Languages, and Programming, ICALP 2017. Muscholl, A., Indyk, P., Kuhn, F. & Chatzigiannakis, I. (eds.). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 9. (Leibniz International Proceedings in Informatics, LIPIcs; vol. 80).
- Fast-Match: Fast Affine Template Matching, Korman, S., Reichman, D., Tsur, G. & Avidan, S., 1 Jan 2017, In: International Journal of Computer Vision. 121, 1, p. 111-125 15 p.
- Coherency Sensitive Hashing, Korman, S. & Avidan, S., 1 Jun 2016, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 38, 6, p. 1099-1112 14 p., 7254191.
- Inverting RANSAC: Global model detection via inlier rate estimation, Litman, R., Korman, S., Bronstein, A. & Avidan, S., 14 Oct 2015, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015. IEEE Computer Society, p. 5243-5251 9 p. 7299161. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 07-12-June-2015).
- Peeking template matching for depth extension, Korman, S., Ofek, E. & Avidan, S., 17 Feb 2015, 2015 International Conference on Computer Vision, ICCV 2015. Institute of Electrical and Electronics Engineers Inc., p. 2174-2182 9 p. 7410608. (Proceedings of the IEEE International Conference on Computer Vision; vol. 2015 International Conference on Computer Vision, ICCV 2015).
- Probably approximately symmetric: Fast rigid symmetry detection with global guarantees, Korman, S., Litman, R., Avidan, S. & Bronstein, A., 1 Feb 2015, In: Computer Graphics Forum. 34, 1, p. 2-13 12 p.
- DCSH-Matching patches in RGBD images, Eshet, Y., Korman, S., Ofek, E. & Avidan, S., 2013, Proceedings - 2013 IEEE International Conference on Computer Vision, ICCV 2013. Institute of Electrical and Electronics Engineers Inc., p. 89-96 8 p. 6751120. (Proceedings of the IEEE International Conference on Computer Vision).
- FasT-match: Fast affine template matching, Korman, S., Reichman, D., Tsur, G. & Avidan, S., 2013, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). p. 2331-2338 8 p.
- Coherency sensitive hashing, Korman, S. & Avidan, S., 2011, 2011 International Conference on Computer Vision, ICCV 2011. p. 1607-1614 8 p. 6126421. (Proceedings of the IEEE International Conference on Computer Vision).
Education
- PhD in Electrical Engineering, Tel Aviv University, supervised by Prof. Shai Avidan.
- MSc in Computer Science, Weizmann Institute of Science, supervised by Prof. Uriel Feige.
- BSc in Mathematics and Computer Science, The Hebrew University of Jerusalem.
Academic Background
Following his PhD at Tel Aviv University, Simon Korman was a postdoctoral researcher at UCLA and subsequently at the Weizmann Institute of Science. Since 2020, he has been a faculty member in the Department of Computer Science at the University of Haifa. His earlier professional experience includes work as an Algorithms Researcher at IoImage and as a Research Intern at Microsoft Research.
Research Areas
- Computer Vision
- Machine Learning and Deep Learning
- Few-Shot Learning
- Representation Learning
- Generative Models
- Image Matching
- 3D Vision