10 results

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Fatma Güney

Ph.D. Student

Advisor: Andreas Geiger

I am interested in estimating 3D scene representations from multi-view video sequences. In particular, I focus on combining semantic segmentation, object detection and classification with 3D reconstruction using efficient inference methods.

Office: S2.017


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Varun Jampani

Ph.D. Student

I am working on leveraging machine learning techniques for better inference in computer vision applications. The main research question is how to make use of learning techniques such as deep neural networks and random forests for inference in structured prediction frameworks.

Office: N3.004


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Joel Janai
(Ph.D. Student)
+49 7071 601 1855
joel.janai@tuebingen.mpg.de
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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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Christoph Lassner

Ph.D. Student

How can autonomous perception discover high-dimensional patterns in recorded data from our environment? I am approaching this question by working on structured computer vision tasks, such as Human Pose Estimation. I hope that insights from this area will improve our data analysis systems, so that they can assist us in better understanding our environment.

Office: N3.004


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Matthew Loper

Ph.D. Student

Advisor: Michael Black

I work on predicting a person's shape and measurements from scan and image data. I specialize in segmentation, evaluation and alignment.


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Thomas Nestmeyer

Ph.D. Student

I work on decomposing photographs into their intrinsic layers of reflectance and shading using deep learning methods for fast inference. In addition I started to work on interactive semantic segmentation using CNNs.

Office: N3.004


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Eric Price

Ph.D. Student

PhD Student, Perceiving Systems. Working on Outdoor 4d scans with multiple UAVs.

Office: N3.004


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Sergey Prokudin

Ph.D. Student

I am working on the intersection of reinforcement learning and computer vision. Many computer vision problems can be posed as sequential decision problems and I aim to use reinforcement learning to solve them.

Office: N3.004


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Anurag Ranjan

Ph.D. Student

Advisor: Michael Black

My research focuses on Deep Learning for dense estimation problems such as Optical Flow. My broad interests include Computer Vision and Machine Learning.

Office: N3.004


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Jonas Wulff

Ph.D. Student

Advisor: Michael Black

My research focuses on the computational analysis of video sequences: In what ways can the temporal dimension of videos be used by a computer to better understand the structure of a scene? And what can we learn from dynamic stimuli processing in the human visual system to make our algorithms more robust?

Office: N3.004