Organizers

Zuzana Kukelova is an assistant professor at the Czech Technical University in Prague (CTU). She received her PhD from CTU in 2013 and her Master in 2005 from Comenius University in Bratislava, Slovakia. She was a Post-Doctoral Researcher at Microsoft Research Cambridge (2014-2016). Zuzana is an expert on solving minimal problems in 3D computer vision and methods for generating efficient solvers for systems of polynomial systems [CVPR’12,’16,’17,’18]. She is the co-author of the first automatic generator of efficient polynomial equation solvers based on Gr ̈obner bases [ECCV’08]. She has worked on absolute and relative camera pose estimation for (par- tially) uncalibrated [CVPR’08,ICCV’13, CVPR’15,ICCV’15,’17,CVPR’18,ICCV’19], semi-generalized [ICCV’21, WACV’23] and rolling shutter cameras [CVPR’15,’16,’20, ECCV’20, ACCV’18, TPAMI’20], as well as solvers based on SIFT correspondences [ICCV’19,ACCV’20,ECCV’22]. Zuzana has co-organized tutorials on minimal problems at ICCV’15 and CVPR’19, was / is an AC for 3DV’18, 3DV’19, ACCV’20, ACCV’22, CVPR’22, and CVPR’23, a program chair for 3DV’20, a general chair for 3DV’22, and will be a program chair for ECCV’26.

Daniel Barath is currently a postdoc at ETH Zurich. He was born in 1989 in Budapest. He had his Ph.D. defense in 2019 at the Eotvos Lorand University, Hungary. Until 2021, he was a member of the Visual Recog- nition Group, FEE, Czech Technical University, Prague, Czech Republic and the Machine Perception Research Laboratory at the Institute for Computer Science and Control (SZTAKI), Budapest, Hungary. Currently, he is a researcher in the Computer Vision and Geometry Group at ETH Zu ̈rich. Also, he is a board member of the Hungarian Association for Image Analysis and Pattern Recognition. His research interests are robust model estimation, minimal methods, and affine correspondences in computer vision. He is an author of most of the recent papers investigating partial or full affine correspondences in their usage for two-view geometry estimation [CVPR’17,CVPR’18,ICCV’19,ICRA’20,ECCV’20,ICRA’21,ICCV’21,ECCV’22,CVPR’23]. He proposed a robust estimator [CVPR’20,CVPR’21,TPAMI’21] that is currently implemented in the widely used OpenCV library and deemed the best-performing estimator by the recent IMC2020 and IMC2021 benchmarks.

Viktor Larsson is an assistant professor at Lund University in Sweden. He received his PhD in mathematics from Lund University in 2018. From 2018 to 2022 he worked as a post-doc and senior researcher at ETH Zurich. He has done extensive work in robust camera calibration [CVPR’18, ICCV’19, CVPR’20, ECCV’20, CVPR’21, CVPR’22] and camera pose estimation (both absolute [CVPR’18, ICCV’19, PAMI’19, ICCV’21, CVPR’22], rel- ative [CVPR’16, ICCV’19, CVPR’20, CVPR’21] and hybrid [WACV’23]). He has also developed methods for constructing minimal solvers [ECCV’16, CVPR’17, ICCV’17, CVPR’18]. He was awarded the Best Paper Award at ACCV’18 and the Best Student Paper Award at ICCV’21. Viktor has previously co-organized tutorials on minimal solvers at CVPR’19 and on benchmarking localization and mapping for AR at ECCV’22. He served as area chair for 3DV’22 and will be local chair for ECCV’26.

Tomas Pajdla received the M.Sc. and Ph.D. from the Czech Technical University in Prague. He works in geom- etry and algebra of computer vision and robotics, with an emphasis on non-classical cameras, 3D reconstruction, and industrial vision. He contributed to the epipolar geometry of panoramic cameras, non-central camera models, generalized epipolar geometries, and to developing solvers for minimal problems in structure from motion. T. Pajdla coauthored papers that received awards at ICCV, CVPR, ACCV, and BMVC. He is a European Computer Vision Association Board member and served as a PC of ECCV and a GC of 3DV. He regularly serves as AC and reviewer of CVPR, ICCV, and ECCV. He participated in organizing many workshops and tutorials at CVPR, ICCV, and ECCV.

Torsten Sattler is a Senior Researcher at CTU. Before, he was a tenured associate professor at Chalmers Uni- versity of Technology. He received a PhD in Computer Science from RWTH Aachen University, Germany, in 2014. From Dec. 2013 to Dec. 2018, he was a post-doctoral and senior researcher at ETH Zurich. Torsten has worked on feature-based localization methods [PAMI’17], long-term localization [CVPR’18,ICCV’19, ECCV’20,CVPR’21] (see also the benchmarks at visuallocalization.net), localization on mobile devices [ECCV’14, IJRR’20], and using semantic scene understanding for localization [CVPR’18, ECCV’18,ICCV’19]. Torsten has co-organized tutorials and workshops at CVPR (’14,’15,’17-’20), ECCV (’18,’20), and ICCV (’17,’19), and was / is an area chair for CVPR (’18,’22,’23), ICCV (’21, ’23), 3DV (’18-’21), GCPR (’19,’21), ICRA (’19,’20), and ECCV (’20). He was a program chair for DAGM GCPR’20, a general chair for 3DV’22, and will be a program chair for ECCV’24.