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16 results

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Andreas Geiger

Professor, University of Tübingen
Max Planck Research Group Leader

I am interested in computer vision and machine learning with a focus on 3D scene understanding, parsing and reconstruction. During my Ph.D. I have developed probabilistic models for 3D traffic scene understanding from movable platforms.

Office: S2.016
+49 7071 601 1830

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Kerstin McGaughey

Personal Assistant

Office: S2.005
+49 7071 601 1911

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Eshed Ohn-Bar

Humboldt Research Fellow

I am interested in computer vision, machine learning, robotics and human-autonomy interaction. I aim to enable intelligent systems (e.g., autonomous vehicles) that can automatically understand and interactively learn from their environment. Towards this goal, I work to address real-world challenges in robust perception and action of safety-critical autonomous systems.

Office: S2.007

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Aseem Behl

Ph.D. Student

Advisor: Andreas Geiger

My research is in the area of Computer Vision and Machine Learning. Currently, I am working on problems related to estimation of 3D motion fields from stereo image sequences.

Office: S2.017

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Kashyap Chitta

Ph.D. Student

My research is in machine learning and computer vision. I am interested in uncertainty estimation, with a focus on explaining errors and improving data efficiency for machine learning algorithms.

Office: S2.007

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Simon Donne

Postdoctoral Researcher

My main interests include computer vision and machine learning. I focus on depth estimation and 3D reconstruction, with a mix between applied and more theoretical research.

Office: S02.007

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Joel Janai

Ph.D. Student

Advisor: Andreas Geiger

Perception is a fundamental part of intelligence since perception is necessary to acquire knowledge and knowledge is necessary to understand perception. Therefore computer vision is one of the most important aspects in the realization of intelligent systems. My interest of research lies in computer vision and the combination with machine learning which, to my mind, will enable the realization of intelligent systems. Currently, I am working on optical flow and how to incorporate high-level information to alleviate this ill-posed problem.

Office: S2.017
+49 7071 601 1855

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Yiyi Liao

Postdoctoral Researcher

Advisor: Andreas Geiger

My research interests include computer vision and deep learning, in especially their applications for semantic and geometric scene understanding in 3D.

Office: S2.013
+49 7071 6011854

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Lars Mescheder

Ph.D. Student

Advisor: Andreas Geiger

I am a PhD student under the joint supervision of Andreas Geiger and Sebastian Nowozin from Microsoft Research. Currently, I am working on generative and probabilistic models in machine learning and computer vision.

Office: S2.017
+49 7071 601 1855

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Michael Niemeyer

Ph.D. Student

My research focuses on continuous representations and generative models.

Office: S2.018

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Michael Oechsle

Ph.D. Student

I am a second-year PhD student supervised by Prof. Andreas Geiger and I am also part of the machine learning team of the ETAS GmbH, Bosch Group. My research focuses on 3D reconstruction and generative models for 3D objects. I am particularly interested in investigating novel object representation that are feasible for learning-based methods.

Office: S2. 004

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Despoina Paschalidou

Ph.D. Student

One of the most challenging tasks of Computer Vision is to endow computers with the ability to discover the underlying relationships between the objects in a scene. The large amount of available labeled data as well as the fast progress in deep learning has significantly advanced many Computer Vision tasks, such as object segmentation. optical flow estimation, action recognition etc. However, a truly intelligent system would ideally be able to infer high-level semantics underlying human actions such as motivation, intent and emotion. However, all human actions involve some uncertainty. To this end, I would like to either develop or to further enhance existing methodologies that incorporate such uncertainties. For now, I have worked on the 3D reconstruction task, by developing a model able to incorporate uncertainties in the image formation process.


Office: S2.013
+49 7071 6011854

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Aditya Prakash

Research Programmer

I am interested in computer vision, deep learning and reinforcement learning. My area of research is in 3D vision and autonomous navigation.

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Paul Sanzenbacher

Research Scientist

Office: N-1.015

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Carolin Schmitt

Ph.D. Student

My research interest lies in the intersection of Computer Vision, Computer Graphics and Machine Learning. Currently I am working on reflectance and material estimation from RGB video input.

Office: S2 013

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Katja Schwarz

Ph.D. Student

My research is at the intersection of Machine Learning, Deep Learning and Computer Vision. Currently, I am interested in 3D geometric scene understanding.

Office: S2.013