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MAGSAC++, a Fast, Reliable and Accurate Robust Estimator.

, , , and . CVPR, page 1301-1309. Computer Vision Foundation / IEEE, (2020)

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Robust Scale-Adaptive Mean-Shift for Tracking., , and . SCIA, volume 7944 of Lecture Notes in Computer Science, page 652-663. Springer, (2013)MAGSAC++, a Fast, Reliable and Accurate Robust Estimator., , , and . CVPR, page 1301-1309. Computer Vision Foundation / IEEE, (2020)Robust scale-adaptive mean-shift for tracking., , and . Pattern Recognit. Lett., (2014)MAGSAC++, a fast, reliable and accurate robust estimator., , , and . CoRR, (2019)Online adaptive hidden Markov model for multi-tracker fusion., , and . Comput. Vis. Image Underst., (2016)The Visual Object Tracking VOT2017 Challenge Results., , , , , , , , , and 94 other author(s). ICCV Workshops, page 1949-1972. IEEE Computer Society, (2017)MAGSAC: Marginalizing Sample Consensus., , and . CVPR, page 10197-10205. Computer Vision Foundation / IEEE, (2019)Online Adaptive Hidden Markov Model for Multi-Tracker Fusion., , and . CoRR, (2015)Marginalizing Sample Consensus., , and . IEEE Trans. Pattern Anal. Mach. Intell., 44 (11): 8420-8432 (2022)Pose-graph via Adaptive Image Re-ordering., , , and . BMVC, page 127. BMVA Press, (2022)