My research spans Computer Vision, Machine Learning, and Graphics. I focus on computing and understanding motion in the world from video. I am particularly interested in human motion -- capturing it from video, using this to learn avatars, and synthesizing natural behavior in novel 3D scenes. I want to build virtual humans that behave and act like real humans.

I am a tenure-track professor (chair 'flight robotics') at the University of Stuttgart. I am also leading the Robot Perception Group at the Perceiving Systems Department. For further information, please visit my personal homepage https://www.aamirahmad.de/.

My research focuses on 3D reconstruction and understanding of humans from 2D images and videos.

Master's Student Intern

I am an ELLIS PhD student jointly at ETH Zurich and the Max Planck Institute for Intelligent Systems, supervised by Prof. Otmar Hilliges and Prof. Michael Black. I am working on reinforcement learning and computer vision.

I am managing our capture facilities and the data collection at the capture hall of the Perceiving Systems Department. I work with computer vision researchers to design, coordinate, schedule and run human subjects trials involving body shape and motion analysis. To collect data we use several computer vision technologies, including our unique 4D body scanner and motion capture facility, and take anthropometric measurements. I am also responsible for ethics, data safety, and lab tours for visitors of the department.

Advisor: Michael Black

I am working in the intersection of Natural Language and Computer Vision. I am particularly interested on analyzing the connection between human motion and language.

Cognitive neuroscientist working at the intersection between biological vision and artificial intelligence

My research focus is body representation. I am interested in basic theoretical frameworks and mechanisms, but also in disturbed body representation. To this end, I conduct behavioral studies in patients with eating disorders or obesity, but also in healthy people.

I'm interested in modeling realistic textures, relighting, 3D reconstruction, and generative modeling.

I am part of the Perceiving Systems department working as a student assistant. Currently, I am doing my master's in Quantitative Data Science at the University of Tübingen and my interests lie in self-supervised learning, statistical machine learning, and computer vision.

I am now a master's student intern at Max Planck Institute for Intelligent Systems.

Advisor: Aamir Ahmad
Michael Black

I am Elia Bonetto, a Ph.D. student at Max Planck Institute for Intelligent Systems in Tübingen, Germany. I am currently enrolled in the IMPRS-IS program under the supervision of Aamir Ahmad, Michael J. Black and Jörg Stückler. My research focuses on the synergy between computer vision and robotics, bridging sensing and action. I want to build systems capable to understand and interact with the world autonomously. My current research focus is on Active SLAM, especially in dynamic environments. I also worked on human body pose estimation, 3D semantic segmentation, autonomous vehicles and robotic arms.

I am a Machine Learning MSc student at University of Tübingen. Previously I was a student assistant at the Perceiving Systems Department, and currently I am writing my Master's thesis here. My research focuses on using contact information for the reconstruction of human-object interactions in 3D from single-view images.

Working at the intersection between digital humans, computer graphics and ML.

(Guest engineer - Visiting from INRIA Grenoble-ALpes' Morpheo team). In collaboration with Sergi Pujades and Marilyn Keller.

Advisor: Michael Black

My goal is to combine the recently emerging field of geometric deep learning for geometry processing with the most effective deep learning concepts (such as GANs) in order to capture and/or generate the most realistic characters.

My main research interests are related to the fusion of visual, structural and semantic information of humans towards achieving a higher level understanding of human behavior. I'm a doctoral fellow in the Max Planck ETH Center for Learning Systems (CLS), a joint program between ETH Zurich and Max Planck Institute for Intelligent Systems. I am supervised by Prof. Otmar Hilliges, Dr. Michael Black and Prof. Bernt Schiele.

Data team Student Assistant

I am a Machine Learning master's student at the University of Tübingen. My research is at the intersection of Human Pose & Shape Estimation, Human-Object Interaction and Human Motion Synthesis. I am especially interested in training motion prior for aforementioned tasks.

Advisor: Michael Black
Dimitris Tzionas

Ph.D. student supervised by Dr. Michael Black in the Perceiving Systems department of the Max Planck Institute for Intelligent Systems in Tübingen, Germany. I am interested in human perception for in-the-wild scenarios and also while interacting with objects.

Advisor: Michael Black

I am a doctoral student at ETH supervised by Dr. Michael J. Black and Prof. Otmar Hilliges. My main research interests lie in human-object interaction.

I'm a Ph.D. student supervised by Prof. Dr. Michael J. Black, interested in computer vision, computer graphics, and machine learning with with a focus on visual inverse problem and controllable generative modeling. More about me at havenfeng.github.io

Advisor: Michael Black

I joined Max Planck ETH Center for Learning Systems as a Ph.D. student in September 2019, where I am supervised by Michael Black and Marc Pollefeys.

Advisor: Michael Black
Katherine Kuchenbecker

I am a Ph.D. student enrolled in the IMPRS-IS program under the supervision of Dr. Katherine J. Kuchenbecker and Dr. Michael J. Black. My main research interests lie in sign language reconstruction and recognition combining vision-based and sensor-based approaches.

I am a Student Assistant for the Data Team at the Perceiving Systems Lab. I am pursuing an M.Sc. of Quantitative Data Science at the Methods Center. My interest mainly lies in intelligent systems in immersive digital experience and Machine Learning for Remote Sensing.

As a trial coordinator at the Perceiving Systems Department, I am mainly responsible for our human subject trials. My core task aims at the collection and processing of anthropometric data such as body shape and motion for scientific studies. Operating various cutting-edge scanning technologies, among which a unique 4D body scanner, is my daily task.

Ph.D. student working with garments.

I am a PhD student at the Max Planck Institute for Intelligent Systems supervised by Prof. Justus Thies and Prof. Gerard Pons-Moll.

Advisor: Michael Black
Sergi Pujades

I am a final-year Ph.D. student at the Max Planck Institute for Intelligent Systems, advised by Professors Sergi Pujades and Michael J. Black. My research focuses on predicting human anatomy from 3D body shapes. During my Ph.D., I also worked at Stanford under the supervision of Karen Liu. I hold a double Master of Science degree from the Karlsruhe Institute of Technology and Grenoble INP Phelma, and I interned at INRIA Grenoble with the MORPHEO team and BBC R&D. Besides digital human modeling, I have also been working on 3D reconstruction, realistic rendering, and virtual reality.

My research concerns learning models of perception and production of non-verbal communicative behavior. Such models can be used to create richer human-robot and human-avatar interaction, for medical diagnosis systems, and for contextual synthesis of different kinds of human behaviors, e.g., guiding synthesis of hand motion from body motion.

Advisor: Michael Black

I am interested in computer vision and machine learning with a focus on human motion understanding.

I am an intern in MPI-IS, Tuebingen, supervised by Prof. Michael J. Black. I am a third-year PhD student (candidate) in MMLab of Nanyang Technological University, Singapore, advised by Prof. Chen Change Loy.

Advisor: Aamir Ahmad

Yu Tang, Liu is interested in Robotics and Control System development. His current work focus on autonomous blimp navigation using reinforcement learning based methods.

I am a PhD visiting student from Mila and University of Montreal, working with in Perceiving Systems department with Prof. Michael Black on generative models for clothed human avatar. Previously I worked with Prof. Bernhard Schölkopf in Empirical Inference department on 3D generative models.

Advisor: Michael Black

I am interested in learning human pose and shape from images and focus on a subset of challenging poses containing self-contact.

Processing motion capture data, tagging and managing data, supporting the data team in setting up camera systems, data captures and events.

I am responsible for collecting and processing data captured with the vicon system, as well as troubleshooting the capture technologies. I am also involved with conducting web based experiments and web based data extractions.

Are there people out there? How do they move? What is their body shape? What are they wearing? For machines to interact with humans and the physical world, we need to train them to answer these questions. My research is focused on combining ideas from computer vision and machine learning to enable machines to perceive humans. During my Ph.D. I worked mostly on geometric modelling and articulated tracking from images.

Advisor: Michael Black
Aamir Ahmad

I am a guest scientist at the department of Perceiving Systems, developing multi-aerial vehicle intelligence for practical research application with prototypes built here at the institute. My current work involves model predictive control of airship formations.

I am working on photo-realistic human 3D avatars. My special interest lies on obtaining such avatars from data that can easily be collected with commodity hardware e.g. monocular RGB videos.

My research aims at understanding the world through the capture and analysis of heterogeneous data (MRI, CT, Point clouds, images, ...) in order to create applied digital instruments, that allow, for example, to generate novel views from a scene, to infer the human shape from a clothed scan, or to predict the amount of adipose tissue of a person from surface observations. To address this challenge, I adopt the approaches of Computer Vision, Signal Processing, Computer Graphics and Statistical Models. My research is often multi-disciplinary, as I need to combine knowledge from these different domains.

Hello, I am Tithi Rakshit, a Student Research Assistant at the Perceiving Systems Department focused on processing motion capture data. I support the data team in cleaning, solving, retargeting, and editing motion capture data, as well as contributing to the set-up and maintenance of scanning systems.

Advisor: Michael Black

As a Ph.D. student at the Max Planck Institute for Intelligent Systems, I have the privilege of being advised by Michael J. Black. Throughout my research journey, I've had the opportunity to collaborate closely with Timo Bolkart and Justus Theis. Additionally, I have done two research internships during my PhD (approximately ~2 years). One is with Google AR hosted by Thabo Beeler, and the other is with Amazon Research mentored by Javier Romero. My work centers on the generation and synthesis of digital humans, delving deep into the intricacies of generative modeling for 3D humans and their clothing, synthesizing human images and reconstructing from monocular images. My fascination for generative modeling has grown immensely in recent years, particularly in the realms of GANs and diffusion models. My research interests encompass the broader scope of generative modeling, aiming to bridge the gap between 2D and 3D human representations and unlock new possibilities in the digital world. Please visit my google scholar page for an updated list of publications. I did my masters from Indian Institute of Science, Bangalore, India before joining my PhD where my focus was mainly on metric learning, face and object recognition.

I am a Ph.D. student intern from Carnegie Mellon University under the supervision of Professor Eni Halilaj. I am particularly interested in estimating 3D motion of humans through video and/or wearables and the integration of biomechanical principles with data-driven models.

Advisor: Michael Black
Dimitris Tzionas

I am a PostDoc researcher in Perceiving Systems at the Max Planck Institute for Intelligent Systems, where I completed my Ph.D. My research focuses on creating Virtual Humans that move and interact with 3D scenes and objects like real humans. My interests include precise motion capture, 3D reconstruction, human-scene interaction, and 3D representation. Recently, I've expanded to include AI topics such as diffusion models and Large Language Models (LLMs) for enhanced object interaction and scene understanding. My goal is to develop human-centered AI that perceives, understands, and generates realistic human actions and interactions for applications in virtual environments.

Justus Thies is the research group leader of the Neural Capture & Synthesis Group.

Advisor: Michael Black

I am a PhD student (2021-) at the Max Planck Institute for Intelligent Systems where I am advised by MPI Director Michael Black. I am interested in 3D modelling of human bodies with limited supervision.

I conduct research on the intersection of Computer Vision, Computer Graphics and Machine Learning. My motivation is to understand and model how people look, move and interact with the world and with each other to perform tasks. The long-term goal is to develop human-centered AI that perceives humans, understands their behavior and helps them to achieve their goals.

My research is focused on human understanding in videos, specifically action recognition, body shape and motion analysis, and sign languages.

I am currently conducting research with Prof. Michael Black as a postdoctoral researcher.

Advisor: Michael Black
Dimitris Tzionas

I am currently a Ph.D. student under the supervision of Prof. Michael J. Black. My research lies in the intersection of vision and graphics, especially in 3D Human Digitalization.

I am currently pursuing his Ph.D. degree in Robotics, Control and Intelligent Systems (EDRS) at École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. I received the B.Eng. degree in Mechanical Engineering with distinction from the Southern University of Science and Technology, Shenzhen, China, in 2020, and the M.Sc. degree in Robotics from the Delft University of Technology, Delft, Netherlands, in 2023. My research interests include multi-modal 3D vision and scene reconstruction for robot perception and scene analysis.

I am a visiting PhD student at the Max Planck Institute for Intelligent Systems. My PhD is at Carnegie Mellon University, advised by Shubham Tulsiani and Abhinav Gupta. In general, I am interested in understanding the physical world from sensors (e.g. images/videos, wearable devices), especially how humans interact with their surroundings in everyday life -- how to accurately perceive the interaction, how to discover patterns of interaction, how to actively interact with the world.

Advisor: Michael Black

I am a PhD student (2020.09-) at the Perceiving Systems Department of Max Planck Institute for Intelligent Systems, jointly supervised by Michael J. Black and Siyu Tang. Before that, I achieved my M.S. in computer applied technology from Peking University in 2020.07 and earned my B.S. in computer science and technology from Beijing University of Posts and Telecommunications in 2017.07. My main research focus is understanding our 3D world with computer vision and machine learning, including 3D human (face reconstruction, mark-less motion capture, motion reconstruction/modeling/generation/prediction), 3D scene reconstruction (Multi-View Stereo), and human-scene interaction.

As a PhD student at the Department of Biological Physics at ELTE University (Budapest, Hungary), I do research in the field of collective behaviour in animal groups from the perpective of movement analysis and computer vision approach.

Advisor: Michael Black

I'm a Ph.D. student in the Max Planck ETH Center for Learning Systems, supervised by Prof. Otmar Hilliges and Dr. Michael Black. I'm currently located in Zurich. Generally, my interest lies in human-centric computer vision and graphics. More specifically, I’m working on 3D animatable models for human bodies and faces.

My research focuses on representing the appearance of people and animals in images and video sequences. I am particularly interested in 2D and 3D models that capture the variability in shape of articulated and deformable objects like the human and animal body. Previous work focused on color image reproduction, multispectral color imaging, readability of colored text.