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14 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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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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Benjamin Coors

Ph.D. Student

Advisor: Andreas Geiger

I'm working on "Efficient Invariant Deep Models for Computer Vision" in cooperation with Bosch.

Office: S2.004
+497071601391


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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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Cusuh Ham

M.S. Intern

I am a Master's student visiting from the Georgia Institute of Technology, where I am advised by Dr. James Hays. My research interests are in computer vision and machine learning.

Office: S2 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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Mengqi Ji

Ph.D. Intern

Mengqi is a Ph.D. student at HKUST, supervised by Prof. Lu Fang (currently in Tsinghua Univ.). From April 2018, he started an internship in MPI hosted by Dr. Andreas Geiger. His primary interest is in 3D reconstruction using DL.

Office: S2.007


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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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Zhaoyang Lv

Ph.D. Intern

Phd student from Georgia Tech, working on 3D scene flow and motion estimation.

Office: S2.007


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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 understanding the visual information given in the world to generate realistic data synthetically. In particular, I am interested in generative modelling with respect to humans. Currently, I investigate how we can employ prior knowledge, e.g. the shape and appearance of the human body, to produce photo-realistic synthetic images.

Office: S2.018


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Michael Oechsle

Ph.D. Student

Since November I am a PhD candidate under the supervision of Prof. Andreas Geiger. Currently I am working on deep generative models in collaboration with the ML team of the ETAS GmbH, a subsidiary of Bosch.

Office: S2. 004
+497071601391


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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.

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Office: S2.013
+49 7071 6011854


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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