Michael Dorkenwald

I am a PhD student in the QUVA lab at the University of Amsterdam supervised by Yuki Asano and Cees Snoek. I am also part of the ELLIS PhD program in cooperation with Qualcomm.

Before, I received my master's degree in physics from Heidelberg University during which I was part of the research group from Björn Ommer. There, I was working on understanding human and object dynamics within generative frameworks primarily for video synthesis. I had the opportunity for a research visit at Kosta Derpanis's lab in Toronto. Furthermore, I completed an internship in the AWS Rekognition team where I worked on self-supervised video representation learning.

Email / Google Scholar / Twitter / Github / LinkedIn

News

[Jul 2024] One paper accepted to ECCV'24 on masked video modeling.
[Jun 2024] Gave a talk at TNO in den Hague and at the National Institute for Informatics in Tokyo.
[Apr 2024] Organizing the workshop "Self Supervised Learning: What is Next?" at ECCV'24.
[Apr 2024] Teaching Assistant for the Foundation Models (FoMo) course.
[Feb 2024] One paper accepted to CVPR'24 on enabling object localisation abilities in VLMs.
[Aug 2023] Started my PhD at University of Amsterdam.
[Jul 2023] Attended the International Computer Vision Summer School in Sicily.

Research

My research primarily revolves around video data, which provides a lens to the intricate dynamics and mechanisms that define our world. I am interested in self-supervised methods and vision-language models as these yield more generalizable visual representations.

	SIGMA: Sinkhorn-Guided Masked Video Modeling Mohammadreza Salehi, Michael Dorkenwald, Fida Mohammad Thoker, Efstratios Gavves, Cees Snoek, Yuki M. Asano Accepted at ECCV 2024* ArXiv / Project Page / Code
	PIN: Positional Insert Unlocks Object Localisation Abilities in VLMs Michael Dorkenwald, Nimrod Barazani, Cees Snoek, Yuki M. Asano CVPR 2024 ArXiv / Project Page / Code
	SCVRL: Shuffled Contrastive Video Representation Learning Michael Dorkenwald, Fanyi Xiao, Biagio Brattoli, Joseph Tighe, Davide Modolo CVPR 2022 I3D-IVU workshop ArXiv / Project Page
	iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis Andreas Blattmann, Timo Milbich, Michael Dorkenwald, Björn Ommer ICCV 2021 ArXiv / Project Page / Code
	Stochastic Image-to-Video Synthesis using cINNs Michael Dorkenwald, Timo Milbich, Andreas Blattmann, Robin Rombach, Konstantinos G. Derpanis, Björn Ommer CVPR 2021 ArXiv / Project Page / Code
	Behavior-Driven Synthesis of Human Dynamics Andreas Blattmann, Timo Milbich, Michael Dorkenwald, Björn Ommer CVPR 2021 ArXiv / Project Page / Code
	Understanding Object Dynamics for Interactive Image-to-Video Synthesis Andreas Blattmann, Timo Milbich, Michael Dorkenwald, Björn Ommer CVPR 2021 ArXiv / Project Page / Code
	Unsupervised behaviour analysis and magnification (uBAM) using deep learning Biagio Brattoli, Uta Buechler, Michael Dorkenwald, Philipp Reiser, Lineard Filli, Fritjof Helmchen, Anna-Sophia Wahl, Björn Ommer Nature Machine Intelligence Article / Project Page / Code
	Unsupervised Magnification of Posture Deviations across Subjects Michael Dorkenwald, Uta Büchler, Björn Ommer CVPR 2020 Article / Project Page