Advisor: Michael Black

Drew is a PhD candidate (2012-present) in Neuroscience at the University of Pennsylvania and a visiting researcher in the Perceiving Systems department of the Max Planck Institute for Intelligent Systems in Tübingen (2015). His research is focused on uncovering the computational principles underlying the organization of networks of cortical neurons to develop general approaches to solving computer vision problems. At Penn, he is investigating computational approaches to understanding visual motion processing under the supervision of Diego Contreras and Kostas Daniilidis.

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My research is devoted to the design of better algorithms for solving computer vision problems as well as their applications in related fields such as computer graphics, medical image analysis and robotics. I have been focusing on the advances of graphical models and the development of graph-based approaches for fundamental computer vision problems, such as segmentation, tracking, shape matching and 3D model inference.

Advisor: Andreas Geiger

I am interested in recovering physical properties of general scenes from images. My current research focuses on reconstructing dense 3-d surface geometry, appearance and motion of dynamic scenes from multi-view image sequences. I believe accurate estimation of these properties will help understand the physical world.

Advisor: Michael Black

My research is related to matching non-rigid articulated objects with emphasis on 3D models of the human body.

Advisor: Andreas Geiger

I am working on object tracking for autonomously driving vehicles. My research interests are focused on optimal object tracking for highly crowded traffic scenes.

Advisor: Andreas Geiger

Advisor: Michael Black

My goal is to apply statistical human body models in various research domains such as psychology, cognitive science, and medicine. A primary goal is to make our body software accessible to more people. For this purpose I interact with various research groups who need body data and software for doing experiments. I manage these relationships, and support the transfer of body shapes as needed.

Advisor: Peter Vincent Gehler

Designing, draping, and animating virtual clothing on realistic body shapes in motion. Human subjects coordination. Human 3D, 4D and motion capture.

My research focuses on human body modeling and 3D mesh registration. In particular, I work on the development of registration algorithms that exploit both 3D shape and texture information. I am also interested in segmentation and registration of medical (namely, dermatologic) images.

I'm the department's friendly neighbourhood Sysadmin. 10000ft tall and made of string.

Advisor: Peter Vincent Gehler

I am interested in efficient inference methods for computer vision. What makes models stand out to allow fast inference and how push the computational burden towards training time? In particular, I am working on human pose estimation from single images, a challenging structured prediction problem.

Advisor: Peter Vincent Gehler

I'm working at the intersection of machine learning and computer vision, developing efficient non-parametric models of human pose, motion, appearance, and segmentation. I'm especially interested in exploiting the additional information provided by the dynamic context present in temporal data sources.

Advisor: Michael Black

My research interest focuses on the use of probabilistic methods in the modeling and representation of shapes and images, and the analysis of biomedical models.

I am interested in modeling nonrigid objects. The geometric relations between a camera and the rigid world are well-known in Multiview Geometry, whereas little is understood about nonrigid objects. Nonrigid geometric concepts can have a huge impact in computer vision in terms of video understanding and in computer graphics in terms of rendering dynamic objects. In particular, I worked on nonrigid structure from motion, representation of nonrigid structures, and 3D human pose estimation.

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.

During my studies in Biology I worked on the relationship between body shape and attractiveness perception. In our department I am responsible for coordinating research trials to collect data on human body shape and pose including 3D body scans and anthropometric measurements. The overall aim is to generate data for the body model as well as other research or art projects.

My research focuses on how intelligent systems can understand a visual world that is constantly changing. Currently my main interest is how to recover fundamental scene properties (i.e. intrinsic images) registered in the pixel grid of the video sequences, such as albedo, shading, optical flow, surface boundaries, and depth.

Advisor: Michael Black

I am interested in Computer Vision and Machine Learning with a focus on temporal analysis, action detection and facial expression analysis. I am also interested in Compressed Sensing and rank minimization for temporal feature representation.

I am a first year PhD student at the Computer Vision and Active Perception Lab, CSC, at KTH. My research focuses on human-human and human-robot interaction and computational models thereof. From mid April to mid Juli 2016 I am doing an internship at the Perceiving Systems Department.

Advisor: Michael Black

I am interested in model-based 3D reconstruction of animals!

Advisor: Gerard Pons-Moll

Research interests: Simulation of deformable object/Mesh processing

My research interests are in capturing, modeling and understanding human face / body. 

Advisor: Gerard Pons-Moll

I'm interested in 3D shape modelling in general. My recent works are looking at novel spaces both for representing shapes in a natural way, and find dense correspondence among shapes in groupwise fashion.