Georg Bökman

According to our database, Georg Bökman authored at least 17 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

From 2D to 3D: AISG-SLA Visual Localization Challenge.

Jialin Gao, Bill Ong, Darld Lwi, Zhen Hao Ng, Xun Wei Yee, Mun-Thye Mak, Wee Siong Ng, See-Kiong Ng, Hui Ying Teo, Victor Khoo, Georg Bökman, Johan Edstedt, Kirill Brodt, Clémentin Boittiaux, Maxime Ferrera, Stepan Konev

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Affine Steerers for Structured Keypoint Description.

Georg Bökman, Johan Edstedt, Michael Felsberg, Fredrik Kahl

Proceedings of the Computer Vision - ECCV 2024, 2024

RoMa: Robust Dense Feature Matching.

Johan Edstedt, Qiyu Sun, Georg Bökman, Mårten Wadenbäck, Michael Felsberg

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

DeDoDe v2: Analyzing and Improving the DeDoDe Keypoint Detector.

Johan Edstedt, Georg Bökman, Zhenjun Zhao

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Steerers: A Framework for Rotation Equivariant Keypoint Descriptors.

Georg Bökman, Johan Edstedt, Michael Felsberg, Fredrik Kahl

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

DeDoDe: Detect, Don't Describe - Describe, Don't Detect for Local Feature Matching.

Johan Edstedt, Georg Bökman, Mårten Wadenbäck, Michael Felsberg

Proceedings of the International Conference on 3D Vision, 2024

2023

In search of projectively equivariant networks.

Georg Bökman, Axel Flinth, Fredrik Kahl

Trans. Mach. Learn. Res., 2023

Leveraging Cutting Edge Deep Learning Based Image Matching for Reconstructing a Large Scene from Sparse Images.

Georg Bökman, Johan Edstedt

CoRR, 2023

ICML 2023 Topological Deep Learning Challenge : Design and Results.

Mathilde Papillon, Mustafa Hajij, Florian Frantzen, Josef Hoppe, Helen Jenne, Johan Mathe, Audun Myers, Theodore Papamarkou, Michael T. Schaub, Ghada Zamzmi, Tolga Birdal, Tamal K. Dey, Tim Doster, Tegan Emerson, Gurusankar Gopalakrishnan, Devendra Govil, Vincent P. Grande, Aldo Guzmán-Sáenz, Henry Kvinge, Neal Livesay, Jan Meissner, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Maneel Reddy Karri, Paul Rosen, Sophia Sanborn, Michael Scholkemper, Robin Walters, Jens Agerberg, Georg Bökman, Sadrodin Barikbin, Claudio Battiloro, Gleb Bazhenov, Guillermo Bernárdez, Aiden Brent, Sergio Escalera, Simone Fiorellino, Dmitrii Gavrilev, Mohammed Hassanin, Paul Häusner, Odin Hoff Gardaa, Abdelwahed Khamis, Manuel Lecha, German Magai, Tatiana Malygina, Pavlo Melnyk, et al.

CoRR, 2023

RoMa: Revisiting Robust Losses for Dense Feature Matching.

Johan Edstedt, Qiyu Sun, Georg Bökman, Mårten Wadenbäck, Michael Felsberg

CoRR, 2023

ICML 2023 Topological Deep Learning Challenge: Design and Results.

Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane

Proceedings of the Topological, 2023

Rigidity Preserving Image Transformations and Equivariance in Perspective.

Lucas Brynte, Georg Bökman, Axel Flinth, Fredrik Kahl

Proceedings of the Image Analysis - 22nd Scandinavian Conference, 2023

Investigating how ReLU-networks encode symmetries.

Georg Bökman, Fredrik Kahl

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

In Search of Projectively Equivariant Neural Networks.

Georg Bökman, Axel Flinth, Fredrik Kahl

CoRR, 2022

Azimuthal Rotational Equivariance in Spherical Convolutional Neural Networks.

Carl Toft, Georg Bökman, Fredrik Kahl

Proceedings of the 26th International Conference on Pattern Recognition, 2022

ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point Clouds.

Georg Bökman, Fredrik Kahl, Axel Flinth

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

A case for using rotation invariant features in state of the art feature matchers.

Georg Bökman, Fredrik Kahl

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022