Lukas Koestler

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 18

Top Topics

Camera Movement

Epipolar Constraint

Vehicle Detection

Top Venues

IEEE Robotics Autom. Lett.

Publications

Simon Klenk, David Bonello, Lukas Koestler, Nikita Araslanov, Daniel Cremers
Masked Event Modeling: Self-Supervised Pretraining for Event Cameras. WACV (2024)
Simon Klenk, Marvin Motzet, Lukas Koestler, Daniel Cremers
Deep Event Visual Odometry. 3DV (2024)
Dominik Muhle, Lukas Koestler, Krishna Murthy Jatavallabhula, Daniel Cremers
Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares. CoRR (2023)
Simon Klenk, Lukas Koestler, Davide Scaramuzza, Daniel Cremers
E-NeRF: Neural Radiance Fields From a Moving Event Camera. IEEE Robotics Autom. Lett. 8 (3) (2023)
Florian Hofherr, Lukas Koestler, Florian Bernard, Daniel Cremers
Neural Implicit Representations for Physical Parameter Inference from a Single Video. WACV (2023)
Simon Klenk, Marvin Motzet, Lukas Koestler, Daniel Cremers
Deep Event Visual Odometry. CoRR (2023)
Dominik Muhle, Lukas Koestler, Krishna Murthy Jatavallabhula, Daniel Cremers
Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares. CVPR (2023)
Dominik Muhle, Lukas Koestler, Nikolaus Demmel, Florian Bernard, Daniel Cremers
The Probabilistic Normal Epipolar Constraint for Frame-To-Frame Rotation Optimization under Uncertain Feature Positions. CoRR (2022)
Simon Klenk, David Bonello, Lukas Koestler, Daniel Cremers
Masked Event Modeling: Self-Supervised Pretraining for Event Cameras. CoRR (2022)
Dominik Muhle, Lukas Koestler, Nikolaus Demmel, Florian Bernard, Daniel Cremers
The Probabilistic Normal Epipolar Constraint for Frame- To-Frame Rotation Optimization under Uncertain Feature Positions. CVPR (2022)
Simon Klenk, Lukas Koestler, Davide Scaramuzza, Daniel Cremers
E-NeRF: Neural Radiance Fields from a Moving Event Camera. CoRR (2022)
Lukas Koestler, Daniel Grittner, Michael Möller, Daniel Cremers, Zorah Lähner
Intrinsic Neural Fields: Learning Functions on Manifolds. CoRR (2022)
Lukas Koestler, Daniel Grittner, Michael Möller, Daniel Cremers, Zorah Lähner
Intrinsic Neural Fields: Learning Functions on Manifolds. ECCV (2) (2022)
Florian Hofherr, Lukas Koestler, Florian Bernard, Daniel Cremers
Neural Implicit Representations for Physical Parameter Inference from a Single Video. CoRR (2022)
Lukas Koestler, Nan Yang, Niclas Zeller, Daniel Cremers
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo. CoRL (2021)
Lukas Koestler, Nan Yang, Niclas Zeller, Daniel Cremers
TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo. CoRR (2021)
Lukas Koestler, Nan Yang, Rui Wang, Daniel Cremers
Learning Monocular 3D Vehicle Detection without 3D Bounding Box Labels. CoRR (2020)
Lukas Koestler, Nan Yang, Rui Wang, Daniel Cremers
Learning Monocular 3D Vehicle Detection Without 3D Bounding Box Labels. GCPR (2020)