Georg Bökman

35 papers A* 6B 1Journal 22Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
Identifiable Equivariant Networks are Layerwise Equivariant.
CoRR
Vahid Shahverdi, Giovanni Luca Marchetti, Georg Bökman, Kathlén Kohn
2025 J jnl
A Framework for Reducing the Complexity of Geometric Vision Problems and its Application to Two-View Triangulation with Approximation Bounds.
CoRR
Felix Rydell, Georg Bökman, Fredrik Kahl, Kathlén Kohn
2025 J jnl
DaD: Distilled Reinforcement Learning for Diverse Keypoint Detection.
CoRR
Johan Edstedt, Georg Bökman, Mårten Wadenbäck, Michael Felsberg
2025 A* conf
Flopping for FLOPs: Leveraging Equivariance for Computational Efficiency.
ICML
Georg Bökman, David Nordström, Fredrik Kahl
2025 J jnl
Flopping for FLOPs: Leveraging equivariance for computational efficiency.
CoRR
Georg Bökman, David Nordström, Fredrik Kahl
2025 J jnl
MuM: Multi-View Masked Image Modeling for 3D Vision.
CoRR
David Nordström, Johan Edstedt, Fredrik Kahl, Georg Bökman
2025 J jnl
Platonic Transformers: A Solid Choice For Equivariance.
CoRR
Mohammad Mohaiminul Islam, Rishabh Anand, David R. Wessels, Friso de Kruiff, Thijs P. Kuipers, Rex Ying, Clara I. Sánchez, Sharvaree Vadgama, Georg Bökman, Erik J. Bekkers
2025 J jnl
RoMa v2: Harder Better Faster Denser Feature Matching.
CoRR
Johan Edstedt, David Nordström, Yushan Zhang, Georg Bökman, Jonathan Astermark, Viktor Larsson, Anders Heyden, Fredrik Kahl, Mårten Wadenbäck, Michael Felsberg
2025 J jnl
Stronger ViTs With Octic Equivariance.
CoRR
David Nordström, Johan Edstedt, Fredrik Kahl, Georg Bökman
2024 — conf
Affine Steerers for Structured Keypoint Description.
ECCV (86)
Georg Bökman, Johan Edstedt, Michael Felsberg, Fredrik Kahl
2024 J jnl
Affine steerers for structured keypoint description.
CoRR
Georg Bökman, Johan Edstedt, Michael Felsberg, Fredrik Kahl
2024 — conf
DeDoDe v2: Analyzing and Improving the DeDoDe Keypoint Detector.
CVPR Workshops
Johan Edstedt, Georg Bökman, Zhenjun Zhao
2024 J jnl
DeDoDe v2: Analyzing and Improving the DeDoDe Keypoint Detector.
CoRR
Johan Edstedt, Georg Bökman, Zhenjun Zhao
2024 — conf
DeDoDe: Detect, Don't Describe - Describe, Don't Detect for Local Feature Matching.
3DV
Johan Edstedt, Georg Bökman, Mårten Wadenbäck, Michael Felsberg
2024 A* conf
From 2D to 3D: AISG-SLA Visual Localization Challenge.
IJCAI
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
2024 J jnl
From 2D to 3D: AISG-SLA Visual Localization Challenge.
CoRR
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
2024 A* conf
RoMa: Robust Dense Feature Matching.
CVPR
Johan Edstedt, Qiyu Sun, Georg Bökman, Mårten Wadenbäck, Michael Felsberg
2024 A* conf
Steerers: A Framework for Rotation Equivariant Keypoint Descriptors.
CVPR
Georg Bökman, Johan Edstedt, Michael Felsberg, Fredrik Kahl
2023 J jnl
DeDoDe: Detect, Don't Describe - Describe, Don't Detect for Local Feature Matching.
CoRR
Johan Edstedt, Georg Bökman, Mårten Wadenbäck, Michael Felsberg
2023 J jnl
ICML 2023 Topological Deep Learning Challenge : Design and Results.
CoRR
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.
2023 — conf
ICML 2023 Topological Deep Learning Challenge: Design and Results.
TAG-ML
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
2023 J jnl
In search of projectively equivariant networks.
Trans. Mach. Learn. Res.
Georg Bökman, Axel Flinth, Fredrik Kahl
2023 A* conf
Investigating how ReLU-networks encode symmetries.
NeurIPS
Georg Bökman, Fredrik Kahl
2023 J jnl
Investigating how ReLU-networks encode symmetries.
CoRR
Georg Bökman, Fredrik Kahl
2023 J jnl
Leveraging Cutting Edge Deep Learning Based Image Matching for Reconstructing a Large Scene from Sparse Images.
CoRR
Georg Bökman, Johan Edstedt
2023 — conf
Rigidity Preserving Image Transformations and Equivariance in Perspective.
SCIA (2)
Lucas Brynte, Georg Bökman, Axel Flinth, Fredrik Kahl
2023 J jnl
RoMa: Revisiting Robust Losses for Dense Feature Matching.
CoRR
Johan Edstedt, Qiyu Sun, Georg Bökman, Mårten Wadenbäck, Michael Felsberg
2023 J jnl
Steerers: A framework for rotation equivariant keypoint descriptors.
CoRR
Georg Bökman, Johan Edstedt, Michael Felsberg, Fredrik Kahl
2022 — conf
A case for using rotation invariant features in state of the art feature matchers.
CVPR Workshops
Georg Bökman, Fredrik Kahl
2022 J jnl
A case for using rotation invariant features in state of the art feature matchers.
CoRR
Georg Bökman, Fredrik Kahl
2022 B conf
Azimuthal Rotational Equivariance in Spherical Convolutional Neural Networks.
ICPR
Carl Toft, Georg Bökman, Fredrik Kahl
2022 J jnl
In Search of Projectively Equivariant Neural Networks.
CoRR
Georg Bökman, Axel Flinth, Fredrik Kahl
2022 J jnl
Rigidity Preserving Image Transformations and Equivariance in Perspective.
CoRR
Lucas Brynte, Georg Bökman, Axel Flinth, Fredrik Kahl
2022 A* conf
ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point Clouds.
CVPR
Georg Bökman, Fredrik Kahl, Axel Flinth
2021 J jnl
ZZ-Net: A Universal Rotation Equivariant Architecture for 2D Point Clouds.
CoRR
Georg Bökman, Fredrik Kahl, Axel Flinth