Michael Dorkenwald

According to our database, Michael Dorkenwald authored at least 15 papers between 2020 and 2025.

Collaborative distances:

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

2025

KV Cache Steering for Inducing Reasoning in Small Language Models.

Max Belitsky, Dawid Jan Kopiczko, Michael Dorkenwald, Muhammad Jehanzeb Mirza, Cees G. M. Snoek, Yuki M. Asano

CoRR, July, 2025

Unsupervised Behavior Analysis and Magnification using Deep Learning: Docker Image.

Biagio Brattoli, Uta Büchler, Michael Dorkenwald, Philipp Reiser, Linard Filli, Fritjof Helmchen, Anna-Sophia Wahl, Björn Ommer

Dataset, February, 2025

GLOV: Guided Large Language Models as Implicit Optimizers for Vision Language Models.

Muhammad Jehanzeb Mirza, Mengjie Zhao, Zhuoyuan Mao, Sivan Doveh, Wei Lin, Paul Gavrikov, Michael Dorkenwald, Shiqi Yang, Saurav Jha, Hiromi Wakaki, Yuki Mitsufuji, Horst Possegger, Rogério Feris, Leonid Karlinsky, James R. Glass

Trans. Mach. Learn. Res., 2025

2024

TVBench: Redesigning Video-Language Evaluation.

Daniel Cores, Michael Dorkenwald, Manuel Mucientes, Cees G. M. Snoek, Yuki M. Asano

CoRR, 2024

SIGMA: Sinkhorn-Guided Masked Video Modeling.

Mohammadreza Salehi, Michael Dorkenwald, Fida Mohammad Thoker, Efstratios Gavves, Cees G. M. Snoek, Yuki M. Asano

Proceedings of the Computer Vision - ECCV 2024, 2024

PIN: Positional Insert Unlocks Object Localisation Abilities in VLMs.

Michael Dorkenwald, Nimrod Barazani, Cees G. M. Snoek, Yuki M. Asano

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

2022

SCVRL: Shuffled Contrastive Video Representation Learning.

Michael Dorkenwald, Fanyi Xiao, Biagio Brattoli, Joseph Tighe, Davide Modolo

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

2021

Unsupervised behaviour analysis and magnification (uBAM) using deep learning Dataset.

Biagio Brattoli, Uta Büchler, Michael Dorkenwald, Philipp Reiser, Linard Filli, Fritjof Helmchen, Anna-Sophia Wahl, Björn Ommer

Dataset, April, 2021

Unsupervised behaviour analysis and magnification (uBAM) using deep learning.

Biagio Brattoli, Uta Büchler, Michael Dorkenwald, Philipp Reiser, Linard Filli, Fritjof Helmchen, Anna-Sophia Wahl, Björn Ommer

Nat. Mach. Intell., 2021

iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis.

Andreas Blattmann, Timo Milbich, Michael Dorkenwald, Björn Ommer

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Stochastic Image-to-Video Synthesis Using cINNs.

Michael Dorkenwald, Timo Milbich, Andreas Blattmann, Robin Rombach, Konstantinos G. Derpanis, Björn Ommer

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Behavior-Driven Synthesis of Human Dynamics.

Andreas Blattmann, Timo Milbich, Michael Dorkenwald, Björn Ommer

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Understanding Object Dynamics for Interactive Image-to-Video Synthesis.

Andreas Blattmann, Timo Milbich, Michael Dorkenwald, Björn Ommer

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

uBAM: Unsupervised Behavior Analysis and Magnification using Deep Learning.

Biagio Brattoli, Uta Büchler, Michael Dorkenwald, Philipp Reiser, Linard Filli, Fritjof Helmchen, Anna-Sophia Wahl, Björn Ommer

CoRR, 2020

Unsupervised Magnification of Posture Deviations Across Subjects.

Michael Dorkenwald, Uta Büchler, Björn Ommer

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020