Fredrik Kahl

About Fredrik Kahl

Fredrik Kahl, With an exceptional h-index of 54 and a recent h-index of 27 (since 2020), a distinguished researcher at Chalmers tekniska högskola, specializes in the field of Computer Vision, Deep Learning, Geometry, Medical Image Analysis.

His recent articles reflect a diverse array of research interests and contributions to the field:

Investigating how ReLU-networks encode symmetries

Improving Open-Set Semi-Supervised Learning with Self-Supervision

TimePillars: Temporally-Recurrent 3D LiDAR Object Detection

Steerers: A framework for rotation equivariant keypoint descriptors

Learning Structure-from-Motion with Graph Attention Networks

Adjustable Visual Appearance for Generalizable Novel View Synthesis

Rigidity preserving image transformations and equivariance in perspective

Privacy-preserving representations are not enough: Recovering scene content from camera poses

Fredrik Kahl Information

University

Position

Professor

Citations(all)

8356

Citations(since 2020)

3755

Cited By

6245

hIndex(all)

54

hIndex(since 2020)

27

i10Index(all)

117

i10Index(since 2020)

69

Email

University Profile Page

Google Scholar

Fredrik Kahl Skills & Research Interests

Computer Vision

Deep Learning

Geometry

Medical Image Analysis

Top articles of Fredrik Kahl

Investigating how ReLU-networks encode symmetries

Advances in Neural Information Processing Systems

2024/2/13

Fredrik Kahl
Fredrik Kahl

H-Index: 29

Improving Open-Set Semi-Supervised Learning with Self-Supervision

2024

TimePillars: Temporally-Recurrent 3D LiDAR Object Detection

arXiv preprint arXiv:2312.17260

2023/12/22

Fredrik Kahl
Fredrik Kahl

H-Index: 29

Steerers: A framework for rotation equivariant keypoint descriptors

arXiv preprint arXiv:2312.02152

2023/12/4

Learning Structure-from-Motion with Graph Attention Networks

arXiv preprint arXiv:2308.15984

2023/8/30

Adjustable Visual Appearance for Generalizable Novel View Synthesis

arXiv preprint arXiv:2306.01344

2023/6/2

David Nilsson
David Nilsson

H-Index: 1

Fredrik Kahl
Fredrik Kahl

H-Index: 29

Rigidity preserving image transformations and equivariance in perspective

2023/4/18

Lucas Brynte
Lucas Brynte

H-Index: 2

Fredrik Kahl
Fredrik Kahl

H-Index: 29

Privacy-preserving representations are not enough: Recovering scene content from camera poses

2023

In search of projectively equivariant networks

arXiv preprint arXiv:2209.14719

2022/9/29

Fredrik Kahl
Fredrik Kahl

H-Index: 29

Azimuthal rotational equivariance in spherical convolutional neural networks

2022/8/21

Carl Toft
Carl Toft

H-Index: 6

Fredrik Kahl
Fredrik Kahl

H-Index: 29

Doublematch: Improving semi-supervised learning with self-supervision

2022/8/21

Development of a novel method to measure bone marrow fat fraction in older women using high-resolution peripheral quantitative computed tomography

Osteoporosis International

2022/7

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

2022

Fredrik Kahl
Fredrik Kahl

H-Index: 29

Zz-net: A universal rotation equivariant architecture for 2d point clouds

2022

Fredrik Kahl
Fredrik Kahl

H-Index: 29

On the tightness of semidefinite relaxations for rotation estimation

Journal of Mathematical Imaging and Vision

2022/1/1

Back to the Feature: Learning Robust Camera Localization from Pixels to Pose

2021

How Privacy-Preserving are Line Clouds? Recovering Scene Details from 3D Lines

2021/3/8

Kunal Chelani
Kunal Chelani

H-Index: 1

Fredrik Kahl
Fredrik Kahl

H-Index: 29

Crowddriven: A new challenging dataset for outdoor visual localization

2021

Carl Toft
Carl Toft

H-Index: 6

Fredrik Kahl
Fredrik Kahl

H-Index: 29

A Quasiconvex Formulation for Radial Cameras

2021

Carl Olsson
Carl Olsson

H-Index: 17

Fredrik Kahl
Fredrik Kahl

H-Index: 29

Long-term visual localization revisited

IEEE Transactions on Pattern Analysis and Machine Intelligence

2020/10/19

See List of Professors in Fredrik Kahl University(Chalmers tekniska högskola)

Co-Authors

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