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. 269-28517 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; vol. 15142 LNCS).
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. 56-6510 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; vol. 2023-June).
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. 12662-1267110 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. 2675-26839 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. 6693-670210 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. 111-12515 p.
Coherency Sensitive Hashing, Korman, S. & Avidan, S., 1 Jun 2016, In: IEEE Transactions on Pattern Analysis and Machine Intelligence.38, 6, p. 1099-111214 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. 5243-52519 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. 2174-21829 p. 7410608. (Proceedings of the IEEE International Conference on Computer Vision; vol. 2015 International Conference on Computer Vision, ICCV 2015).
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. 89-968 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. 2331-23388 p.
Coherency sensitive hashing, Korman, S. & Avidan, S., 2011, 2011 International Conference on Computer Vision, ICCV 2011.p. 1607-16148 p. 6126421. (Proceedings of the IEEE International Conference on Computer Vision).
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