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ORCIDGeorg Bökman
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2020 – today
- 2025
[i16]Georg Bökman, David J. Nordstrom, Fredrik Kahl:
Flopping for FLOPs: Leveraging equivariance for computational efficiency. CoRR abs/2502.05169 (2025)- [i15]Johan Edstedt, Georg Bökman, Mårten Wadenbäck, Michael Felsberg:
DaD: Distilled Reinforcement Learning for Diverse Keypoint Detection. CoRR abs/2503.07347 (2025) - [i14]Felix Rydell, Georg Bökman, Fredrik Kahl, Kathlén Kohn:
A Framework for Reducing the Complexity of Geometric Vision Problems and its Application to Two-View Triangulation with Approximation Bounds. CoRR abs/2503.08142 (2025) - 2024
- [c12]Johan Edstedt, Georg Bökman, Mårten Wadenbäck, Michael Felsberg:
DeDoDe: Detect, Don't Describe - Describe, Don't Detect for Local Feature Matching. 3DV 2024: 148-157 - [c11]Johan Edstedt, Georg Bökman, Zhenjun Zhao:
DeDoDe v2: Analyzing and Improving the DeDoDe Keypoint Detector. CVPR Workshops 2024: 4245-4253 - [c10]Georg Bökman, Johan Edstedt, Michael Felsberg, Fredrik Kahl:
Steerers: A Framework for Rotation Equivariant Keypoint Descriptors. CVPR 2024: 4885-4895 - [c9]Johan Edstedt, Qiyu Sun, Georg Bökman, Mårten Wadenbäck, Michael Felsberg:
RoMa: Robust Dense Feature Matching. CVPR 2024: 19790-19800 - [c8]Georg Bökman, Johan Edstedt, Michael Felsberg, Fredrik Kahl:
Affine Steerers for Structured Keypoint Description. ECCV (86) 2024: 449-468 - [c7]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:
From 2D to 3D: AISG-SLA Visual Localization Challenge. IJCAI 2024: 8661-8664 - [i13]Johan Edstedt, Georg Bökman, Zhenjun Zhao:
DeDoDe v2: Analyzing and Improving the DeDoDe Keypoint Detector. CoRR abs/2404.08928 (2024) - [i12]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:
From 2D to 3D: AISG-SLA Visual Localization Challenge. CoRR abs/2407.18590 (2024) - [i11]Georg Bökman, Johan Edstedt, Michael Felsberg, Fredrik Kahl:
Affine steerers for structured keypoint description. CoRR abs/2408.14186 (2024) - 2023
- [j1]Georg Bökman, Axel Flinth, Fredrik Kahl:
In search of projectively equivariant networks. Trans. Mach. Learn. Res. 2023 (2023) - [c6]Georg Bökman, Fredrik Kahl:
Investigating how ReLU-networks encode symmetries. NeurIPS 2023 - [c5]Lucas Brynte
, Georg Bökman, Axel Flinth, Fredrik Kahl:
Rigidity Preserving Image Transformations and Equivariance in Perspective. SCIA (2) 2023: 59-76 - [c4]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:
ICML 2023 Topological Deep Learning Challenge: Design and Results. TAG-ML 2023: 3-8 - [i10]Johan Edstedt, Qiyu Sun, Georg Bökman, Mårten Wadenbäck, Michael Felsberg:
RoMa: Revisiting Robust Losses for Dense Feature Matching. CoRR abs/2305.15404 (2023) - [i9]Georg Bökman, Fredrik Kahl:
Investigating how ReLU-networks encode symmetries. CoRR abs/2305.17017 (2023) - [i8]Johan Edstedt, Georg Bökman, Mårten Wadenbäck, Michael Felsberg:
DeDoDe: Detect, Don't Describe - Describe, Don't Detect for Local Feature Matching. CoRR abs/2308.08479 (2023) - [i7]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.:
ICML 2023 Topological Deep Learning Challenge : Design and Results. CoRR abs/2309.15188 (2023) - [i6]Georg Bökman, Johan Edstedt:
Leveraging Cutting Edge Deep Learning Based Image Matching for Reconstructing a Large Scene from Sparse Images. CoRR abs/2310.01092 (2023) - [i5]Georg Bökman, Johan Edstedt, Michael Felsberg, Fredrik Kahl:
Steerers: A framework for rotation equivariant keypoint descriptors. CoRR abs/2312.02152 (2023) - 2022
- [c3]Georg Bökman, Fredrik Kahl:
A case for using rotation invariant features in state of the art feature matchers. CVPR Workshops 2022: 5106-5115 - [c2]Georg Bökman, Fredrik Kahl, Axel Flinth:
ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point Clouds. CVPR 2022: 10966-10975 - [c1]Carl Toft, Georg Bökman, Fredrik Kahl:
Azimuthal Rotational Equivariance in Spherical Convolutional Neural Networks. ICPR 2022: 3808-3814 - [i4]Lucas Brynte, Georg Bökman, Axel Flinth, Fredrik Kahl:
Rigidity Preserving Image Transformations and Equivariance in Perspective. CoRR abs/2201.13065 (2022) - [i3]Georg Bökman, Fredrik Kahl:
A case for using rotation invariant features in state of the art feature matchers. CoRR abs/2204.10144 (2022) - [i2]Georg Bökman, Axel Flinth, Fredrik Kahl:
In Search of Projectively Equivariant Neural Networks. CoRR abs/2209.14719 (2022) - 2021
- [i1]Georg Bökman, Fredrik Kahl, Axel Flinth:
ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point Clouds. CoRR abs/2111.15341 (2021)
Coauthor Index
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