Michael Black
Managing Director
Max-Planck-Ring 4
72076 Tübingen
Germany
Curriculum Vitae
Conflict of Interest Disclosure
This includes any corporate activity within the last 5 years involving more than $5000 where I have a personal or professional interest or any role in which I have corporate responsibility.
- Corporate research funding (unrestricted): Intel, NVIDIA, Meta/Facebook, and Amazon.
- Financial interests (e.g. stock): Amazon, Datagen Technologies, Meshcapade.
- Commercial licensing of MPI technology where I am a co-inventor.
- Side employment: Meshcapade (20%, Dec. 2022-present), Amazon (20%, 2017-2021), Body Labs Inc (20%, 2013-2017).
- Corporate boards: Body Labs Inc. (2013-2017).
Citations
Blog
Video
Social Media
Biography
Michael J. Black received his B.Sc. from the University of British Columbia (1985), his M.S. from Stanford (1989), and his Ph.D. in computer science from Yale University (1992). After research at NASA Ames and post-doctoral research at the University of Toronto, he joined the Xerox Palo Alto Research Center in 1993 where he later managed the Image Understanding Area and founded the Digital Video Analysis group. From 2000 to 2010 he was on the faculty of Brown University in the Department of Computer Science (Assoc. Prof. 2000-2004, Prof. 2004-2010). He is an Honorarprofessor at the University of Tuebingen and a founding director at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, where he leads the Perceiving Systems department and serves as Managing Director. He was a Distinguished Amazon Scholar (VP, 2017-2021).
Black is a member of the German National Academy of Sciences Leopoldina and a foreign member of the Royal Swedish Academy of Sciences. He is a recipient of the PAMI Distinguished Researcher Award and all three major test-of-time awards in the field, including the 2022 and 2010 Koenderink Prize (ECCV), the 2013 Helmholtz Prize (ICCV), and the 2020 Longuet-Higgins Prize (CVPR). His work has won several paper awards including the IEEE Computer Society Outstanding Paper Award (CVPR'91). His work received Honorable Mention for the Marr Prize in 1999 and 2005. His early work on optical flow has been widely used in Hollywood films including for the Academy-Award-winning effects in “What Dreams May Come” and “The Matrix Reloaded.” He has contributed to several influential datasets including the Middlebury Flow dataset, HumanEva, and the Sintel dataset. Black has coauthored over 300 peer-reviewed scientific publications.
He is also active in commercializing scientific results, is an inventor on 10 issued patents, and has advised multiple startups. He uniquely combines computer vision, graphics, and machine learning to create digital humans. In 2013, he co-founded Body Labs Inc., which used computer vision, machine learning, and graphics technology licensed from his lab to commercialize "the body as a digital platform." Body Labs was acquired by Amazon in 2017. Black is a co-founder and Chief Scientist of Meshcapade GmbH, where he is building human-centered foundation models that perceive, understand and generate 3D human behavior.
Short
Michael Black received his B.Sc. from the University of British Columbia (1985), his M.S. from Stanford (1989), and his Ph.D. from Yale University (1992). After post-doctoral research at the University of Toronto, he worked at Xerox PARC as a member of research staff and area manager. From 2000 to 2010 he was on the faculty of Brown University in the Department of Computer Science (Assoc. Prof. 2000-2004, Prof. 2004-2010). He is an Honorarprofessor at the University of Tübingen and one of the founding directors at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, where he leads the Perceiving Systems department and serves as Managing Director. He was also a Distinguished Amazon Scholar (VP, 2017-2021). He is a recipient of the PAMI Distinguished Researcher Award and all three major test-of-time awards in Computer Vision, including the 2022 and 2010 Koenderink Prize, the 2013 Helmholtz Prize, and the 2020 Longuet-Higgins Prize. He is a member of the German National Academy of Sciences Leopoldina and a foreign member of the Royal Swedish Academy of Sciences. In 2013 he co-founded Body Labs Inc., which was acquired by Amazon in 2017. Black is a co-founder and Chief Scientist of Meshcapade GmbH.
Shorter (150 words)
Michael Black received a B.Sc. from the University of British Columbia (1985), M.S. from Stanford (1989), and Ph.D. from Yale University (1992). He held positions at the University of Toronto, Xerox PARC, and Brown University. He is an Honorarprofessor at the University of Tübingen and one of the founding directors at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, where he leads the Perceiving Systems department and serves as Managing Director. He was a Distinguished Amazon Scholar (2017-2021). He is a recipient of the PAMI Distinguished Researcher Award, the 2022 and 2010 Koenderink Prize, the 2013 Helmholtz Prize, and the 2020 Longuet-Higgins Prize. He is a member of the German National Academy of Sciences Leopoldina and a foreign member of the Royal Swedish Academy of Sciences. In 2013 he co-founded Body Labs Inc., which was acquired by Amazon in 2017. He is co-founder and Chief Scientist of Meshcapade.
Shortest (100 words)
Michael Black received his B.Sc. from the University of British Columbia (1985), M.S. from Stanford (1989), and Ph.D. from Yale (1992). He held positions at the University of Toronto, Xerox PARC, Brown, and Amazon. He is an Honorarprofessor at the University of Tübingen and a founding director at the Max Planck Institute for Intelligent Systems. He is a recipient of the PAMI Distinguished Researcher Award, the 2022 and 2010 Koenderink Prize, the 2013 Helmholtz Prize, and the 2020 Longuet-Higgins Prize. He is a member of two national academies (Germany and Sweden). He has co-founded two companies: Body Labs and Meshcapade.
Head shot
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Education
Yale University, New Haven, CT
Ph.D., Computer Science, 1992.
Stanford University, Stanford, CA
M.S., Computer Science, 1989.
The University of British Columbia, Vancouver, BC
B.Sc., Honours Computer Science, 1985.
Selected Awards/Honors
2023 PAMI Distinguished Researcher Award.
2022 Koenderink Prize for Fundamental Contributions in Computer Vision, for the paper "A naturalistic open source movie for optical flow evaluation", by Butler, D. J. and Wulff, J. and Stanley, G. B. and Black, M. J.
Best Paper Award, German Conference on Pattern Recognition, GCPR 2022, for the paper "InvGAN: Invertible GANs", by Partha Ghosh, Dominik Zietlow, Michael J. Black, Larry S. Davis, Xiaochen Hu.
Max-Planck-Gründungspreis des Stifterverbandes, Science Prize 2022 in the Entrepreneurship category, to Naureen Mahmood, Talha Zaman, and Michael J. Black for the Meshcapade GmbH team, in recognition of this successful spin-off and the particularly high impact on society. Berlin, June 21, 2022.
German National Academy of Sciences Leopoldina
Member since May 2021.
2020 Longuet-Higgins Prize
for the paper Sun, D., Roth, S., Black, M. J., “Secrets of optical flow estimation and their principles,” In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 2432–2439, IEEE, June 2010.
Alumni Research Award
University of British Columbia, Department of Computer Science, 2018.
Royal Swedish Academy of Sciences
Foreign member, Class for Engineering Sciences, since June 2015.
2013 Helmholtz Prize
for the paper: Black, M. J., and Anandan, P., "A framework for the robust estimation of optical flow,'' IEEE International Conference on Computer Vision, ICCV, pages 231-236, Berlin, Germany. May 1993.
2010 Koenderink Prize for Fundamental Contributions in Computer Vision,
with Sidenbladh, H. and Fleet, D. J. for the paper "Stochastic tracking of 3D human figures using 2D image motion,'' European Conference on Computer Vision, 2000.
Best Paper Award, Eurographics 2017, for the paper "Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs", by von Marcard, T., Rosenhahn, B., Black, M. J., Pons-Moll, G.
"Dataset Award" at the Eurographics Symposium on Geometry Processing 2016, with F. Bogo, J. Romero, and M. Loper, for the paper "FAUST: Dataset and evaluation for 3D mesh registration," CVPR 2014.
Best Paper Award, International Conference on 3D Vision (3DV), 2015, with A. O. Ulusoy and A. Geiger, for the paper "Towards Probabilistic Volumetric Reconstruction using Ray Potentials."
Best Paper Award, INI-Graphics Net, 2008, First Prize Winner of Category Research,
with S. Roth for the paper "Steerable random fields."
Best Paper Award, Fourth International Conference on Articulated Motion and Deformable Objects (AMDO-e 2006), with L. Sigal for the paper "Predicting 3D people from 2D pictures.''
Marr Prize, Honorable Mention, Int. Conf. on Computer Vision, ICCV-2005, Beijing, China, Oct. 2005 with S. Roth for the paper "On the spatial statistics of optical flow.''
Marr Prize, Honorable Mention, Int. Conf. on Computer Vision, ICCV-99, Corfu, Greece, Sept. 1999 with D. J. Fleet for the paper "Probabilistic detection and tracking of motion discontinuities.''
IEEE Computer Society, Outstanding Paper Award, Conference on Computer Vision and Pattern Recognition, Maui, Hawaii, June 1991 with P. Anandan for the paper "Robust dynamic motion estimation over time.''
Commendation and Chief's Award, Henrico County Division of Police,
County of Henrico, Virginia, April 19, 2007.
University of Maryland, Invention of the Year, 1995, "Tracking and Recognizing Facial Expressions,'' with Y. Yacoob.
University of Toronto, Computer Science Students' Union Teaching Award for 1992-1993.
Employment and Positions Held
Max Planck Institute for Intelligent Systems
Tübingen, Germany
Director, 1/11 - present
Managing Director, 7/23 - present, 2/13 - 6/15, 3/18 - 11/18
Meshcapade
Tübingen, Germany
Chief Scientist (Dec. 2022-present) and co-founder.
Amazon
Tübingen, Germany
Distinguished Amazon Scholar (VP Technology - Software Dev), 11/17 - 12/21
Eberhard Karls Universität Tübingen, Faculty of Science, Department of Computer Science
Tübingen, Germany
Honorarprofessor, 05/22/12 - present
Body Labs Inc.
New York, NY, USA
Co-founder, Science Advisor, Member of the Board, 01/13 - 10/2017
ETH Zürich, Dept. of Information Technology and Electrical Engineering
Zürich, Switzerland
Visting Professor, 04/2014 - 04/2016
Stanford University, Electrical Engineering
Stanford, CA
Visiting Professor, 5/11-4/12, 7/12-7/13
Brown University, Department of Computer Science,
Providence, RI
Adjunct Professor (Research), 1/11-present
Professor, 7/04-12/10
Associate Professor, 7/00-6/04
My research addressed the problem of estimating and explaining motion in image sequences. I developed methods detecting and tracking 2D and 3D human motion including the introduction of particle filtering for 3D human tracking and belief propagation for 3D human pose estimation. I worked on probabilistic models of images include the high-order Field of Experts model. I worked on 3D human shape estimation from images and video and developed applications of this technology. I also developed mathematical models for decoding neural signals. This included the first uses of particle filtering and Kalman filtering for decoding motor cortical neural activity and the first point-and-click cortical neural brain-machine-interface for people with paralysis.
Xerox Palo Alto Research Center,
Palo Alto, CA
Area Manager, Image Understanding Area, 1/96-7/00
Member of Research Staff, 9/93-12/95
Research included modeling image changes (motion, illumination, specularity, occlusion, etc.) in video as a mixture of causes. I developed methods of motion explanation; that is, the extraction of mid-level or high-level concepts from motion. This included the modeling and recognition of motion "features" (occlusion boundaries, moving bars, etc.), human facial expressions and gestures, and motion "texture" (plants, fire, water, etc.). I applied these methods to problems in video indexing, motion for video annotation, teleconferencing, and gestural user interfaces. Other research included robust learning of image-based models, regularization with transparency, anisotropic diffusion, and the recovery of multiple shapes from transparent textures.
University of Toronto,
Toronto, Ontario
Assistant Professor, Department of Computer Science, (8/92 - 9/93).
Research included the application of mixture models to optical flow, detection and tracking of surface discontinuities using motion information, and robust surface recovery in dynamic environments.
Yale University, (9/89-8/92)
New Haven, CT
Research Assistant, Department of Computer Science.
Research in the recovery of optical flow, incremental estimation, temporal continuity, applications of robust statistics to optical flow, the relationship between robust statistics and line processes, the early detection of motion discontinuities, and the role of representation in computer vision.
NASA Ames Research Center, (6/90-8/92)
Moffett Field, CA
Visiting Researcher, Aerospace Human Factors Research Division.
Developed motion estimation algorithms in the context of an autonomous Mars landing and nap-of-the-earth helicopter flight and studied the psychophysical implications of a temporal continuity assumption.
Advanced Decision Systems, (12/86-6/89)
Mountain View, CA
Computer Scientist, Image Understanding Group.
Research on spatial reasoning for robotic vehicle route planning and terrain analysis. Vision research including perceptual grouping, object-based translational motion processing, the integration of vision and control for an autonomous vehicle, object modeling using generalized cylinders, and the development of an object-oriented vision environment.
GTE Government Systems, (6/85-12/86)
Mountain View, CA
Engineer, Artificial Intelligence Group.
Developed expert systems for multi-source data fusion and fault location.
Miscellaneous, ('78-'85)
Summer undergraduate researcher at UBC; park ranger's assistant; volunteer firefighter, busboy; and probably my worst job: cleaning dog kennels.
Research Interests
I am interested in motion. What does motion tell us about the structure of the world and how can we compute this from video? How do humans and animals move? What goals drive behavior? My work combines computer vision, graphics and machine learning to develop new models and algorithms to capture, analyze, and synthesize the motion of humans, animals and the world.
My Computer Vision research addresses:
- articulated human motion pose estimation and tracking;
- the estimation of human body shape from images and video;
- the estimation of scene structure and physical properties from video;
- the estimation of optical flow;
- vision as inverse graphics.
My Graphics research addresses:
- virtual humans;
- next-generation motion capture;
- articulated and non-rigid shape representation;
- human and animal shape and motion capture;
- human animation, AR/VR, and Metaverse applications;
- capture and animation of clothing.
My Machine Learning reserarch addresses
- learning representations of 3D shape
- implicit functions
- neural rendering
- regressing 3D models from images
- temporal models of human motion
- learning 3D models from 2D data
I also work on industrial applications in Fashion Science:
- Body scanning and measurement;
- clothing sizing;
- cloth capture and modeling;
- virtual try-on.
My previous work on Computational Neuroscience research addressed:
- modeling the neural control of reaching and grasping;
- novel neural decoding algorithms;
- neural prostheses and cortical brain-machine interfaces;
- markless animal motion capture.
What ties this all together is my ultimate goal of understanding humans and their behavior by creating vritual humans. If we can can simulate a virtual human that behaves like a real human, then we have a working model of ourselves.
Current PhD students:
Shrisha Bharadwaj, Max Planck Institute for Intelligent Systems, co-supervised with Victoria Fernandez Abrevaya.
Vanessa Sklyarova, MPI-ETH Center for Learning Systems, co-supervised with Otmar Hilliges and Justus Thies.
Peter Kulits, MPI for Intelligent Systems, co-supervised with Silvia Zuffi
Artur Grigorev, MPI-ETH Center for Learning Systems, co-supervised with Otmar Hilliges
Markos Diomataris, MPI-ETH Center for Learning Systems, co-supervised with Otmar Hilliges and Bernt Schiele
Mert Albaba, MPI-ETH Center for Learning Systems, co-supervised with Otmar Hilliges
Sai Kumar Dwivedi, Max Planck Institute for Intelligent Systems, Co-supervised with Dimitris Tzionas
Haiwen Feng, Max Planck Institute for Intelligent Systems
Yufeng Zheng, MPI-ETH Center for Learning Systems, Co-supervised with Otmar Hilliges
Yuliang Xiu, Max Planck Institute for Intelligent Systems, Co-supervised with Dimitris Tzionas
Radek Danecek, Max Planck Institute for Intelligent Systems, Co-supervised with Timo Bolkart
Shashank Tripathi, Max Planck Institute for Intelligent Systems
Zicong Fan (Alex), MPI-ETH Center for Learning Systems, Co-supervised with Otmar Hilliges
Hongwei Yi, Max Planck Institute for Intelligent Systems, Tuebingen AI Center, Co-supervised with Siyu Tang
Maria Paola Forte, Max Planck Institute for Intelligent Systems, Co-supervised with Katherin Kuchenbecker
Nikos Athanasiou, Max Planck Graduate Center for Computer and Information Science, Co-supervised with Gül Varol
Yao Feng, MPI-ETH Center for Learning Systems, Co-supervised with Marc Pollefeys and Timo Bolkart
Marilyn Keller, MPI for Intelligent Systems, Co-supervised with Sergi Pujades
Muhammad Kocabas, MPI-ETH Center for Learning Systems, Co-supervised with Otmar Hilliges
Eric Price, MPI for Intelligent Systems, Tübingen, Co-supervised with Aamir Ahmad
Former PhD students:
Soubhik Sanyal, Thesis: Leveraging Unpaired Data for the Creation of Controllable Digital Humans, Int. Max Planck Research School, Intelligent Systems (IMPRS-IS), Tübingen
Ahmed Osman, Thesis: Realistic Digital Human Characters: Challenges, Models and Training Algorithms, Int. Max Planck Research School, Intelligent Systems, Tübingen
Omid Taheri, Thesis: Modeling Dynamic 3D Human-Object Interactions: From Capture to Synthesis, MPI for Intelligent Systems, Tübingen, Co-supervised with Dimitris Tzionas
Mathis Petrovich, Thesis: Natural Language Control for 3D Human Motion Synthesis
École des Ponts ParisTech (ENPC), Co-supervised with Gül Varol
Lea Müller, PostDoc, UC Berkeley
Thesis: Self- and Interpersonal Contact in 3D Human Mesh Reconstruction.
Int. Max Planck Research School, Intelligent Systems, Tübingen
Qianli Ma, NVIDIA Research
Thesis: Neural Shape Modeling of 3D Clothed Humans, Int. Max Planck Research School, Intelligent Systems, Tübingen, Co-supervised with Siyu Tang
Nadine Rüegg, Meta
Thesis: Monocular 3D Shape and Pose Estimation for Humans and Animals. MPI-ETH Center for Learning Systems, Co-supervised with Konrad Schindler
Xu Chen, Google Zürich.
Thesis: Learning Clothed 3D Human Models with Articulated Neural Implicit Representations. MPI-ETH Center for Learning Systems, Co-supervised with Otmar Hilliges and Andreas Geiger. July 2023.
Mohamed Hassan, Electronic Arts.
Thesis: Reconstruction and Synthesis of Human-Scene Interaction. Co-supervised with Dimitris Tzionas. Feb. 2023.
Yinghao Huang, MPI for Intelligent Systems, Tübingen.
Thesis: Whole-Body Motion Capture and Beyond: From Model-Based Inference to Learning-Based Regression. Co-supervised with Dimitris Tzionas. Dec. 2022
Vassilis Choutas, Google Zürich,
Thesis: Towards more Realistic Model-Based 3D Human Reconstrution. Co-supervised with Luc van Gool and Dimitris Tzionas, Dec. 2022
Partha Ghosh, Post doc in Emperical Inference, Intelligent Systems, Tübingen.
Thesis: Towards more Realistic Model-Based 3D Human Reconstrution, Nov. 2022
Joel Janai, Bosch
Thesis: Addressing the Data Scarcity of Learning-based Optical Flow Approaches, University of Tübingen. Co-supervised with Andreas Geiger, April 2020
Anurag Ranjan, Reseaercher, Apple Machine Intelligence,
Thesis: Towards Geometric Understanding of Motion, University of Tübingen, Dec 2019
Daniel Cudeiro, Deceased
Jonas Wulff, ML Lead, Xyla
Thesis: Model-based Optical Flow: Layers, Learning, and Geometry, University of Tübingen, April 2018
Matthew Loper,
Thesis: Human Shape Estimation using Statistical Body Models, University of Tübingen, May 2017
Silvia Zuffi, Research Scientist, IMATI-CNR, Institute for Applied Mathematics and Information Technologies, Milan Italy
Thesis: Shape Models of the Human Body for Distributed Inference, Brown University, May 2015
Aggeliki Tsoli, Computer Vision Research Engineer, Uplift Labs,
Thesis: Modeling the Human body in 3D: Data Registration and Human Shape Representation, Department of Computer Science, Brown University, May 2014
Oren Freifeld, Assistant Professor, Dept. of Computer Science, Ben-Gurion Univ., Israel,
Thesis: Statistics on Manifolds with Applications to Modeling Shape Deformations, Division of Applied Mathematics, Brown University, August 2013
Peng Guan, Senior Software Engineer, Google,
Thesis: Virtual Human Bodies with Clothing and Hair: From Images to Animation, Department of Computer Science, Brown University, December 2012
Deqing Sun, Senior Research Scientist, Google,
Thesis: From Pixels to Layers: Joint Motion Estimation and Segmentation, Department of Computer Science, Brown University, July 2012
Alexandru Balan, Xbox Incubation Researcher, Microsoft
Thesis: Detailed Human Shape and Pose from Images, Department of Computer Science, Brown University, May 2010
Leonid Sigal, Associate Professor of Computer Science, Univ. of British Columbia (UBC)
Thesis: Continuous-state graphical models for object localization, pose estimation and tracking Department of Computer Science, Brown University, May 2008
Stefan Roth, Professor, Dept. of Computer Science, TU Darmstadt
Thesis: High-order Markov random fields for low-level vision. Dept. of Computer Science, Brown University,
May 2007 Winner of the Joukowsky Family Foundation Outstanding Dissertation Award
Frank Wood, Associate Professor of Computer Science, Univ. of British Columbia (UBC)
Thesis: Nonparametric Bayesian modeling of neural data. Department of Computer Science, Brown University
Hulya Yalcin, Assistant Professor, Department of Electronics and Communications Engineering, Istanbul Technical University, Turkey
Thesis: Implicit models of moving and static surfaces, Division of Engineering, Brown University, May 2004
Wei Wu, Professor, Dept. of Statistics, Florida State
Thesis: Statistical models of neural coding in motor cortex, Division of Applied Math, Brown University. Co-supervised with David Mumford. May 2004.
Fernando De la Torre, Associate Research Professor, CMU
Thesis: Robust subspace learning for computer vision, La Salle School of Engineering. Universitat Ramon Llull, Barcelona, Spain. Jan. 2002
Hedvig Kjellstrom (nee Sidenbladh), Professor of Comptuer Science, KTH, Sweden
Thesis: Probabilistic Tracking and Reconstruction of 3D Human Motion in Monocular Video Sequences. Dept. of Numerical Analysis and Computer Science, KTH, Stockholm, Sweden 2001
Shanon Ju (with Allan Jepson)
Thesis: Estimating image motion in layers: The Skin and Bones model. University of Toronto. Jan. 1999
Post doctoral researchers and research scientists:
- Yandong Wen, MPI for Intelligent Systems, June. 2022 - present
- Victoria Fernández Abrevaya, MPI for Intelligent Systems, Sept. 2020 - present
Former post doctoral researchers and research scientists:
- Timo Bolkart, Google Zürich
- Arjun Chandrasekaran, CONXAI
- Jinlong Yang, Google Zürich
- Chun-Hao Paul Huang, Adobe Research, London
- Dimitris Tzionas, Assistant Professor, Univ. of Amsterdam.
- Aamir Ahmad, Assistant Professor at Univ of Stuttgart.
- Siyu Tang, Assistant Professor at ETH Zürich.
- Sergi Pujades, Associate Professor at Université Grenoble Alpes.
- Alejandra Quiros-Ramirez, Postdoc, Dept. of Psychology, Univ. of Konstanz.
- Laura Sevilla, Reader (Associate Professor) in Image and Vision Computing, University of Edinburgh.
- Ali Osman Ulusoy, (jointly with A. Geiger), Senior Software Engineer, Google.
- Stephan Streuber, Professor, Coburg University
- Naejin Kong, Staff Scientist, Samsung, Korea.
- Federica Bogo, Meta Reality Labs Zurich.
- Gerard Pons-Moll, Professor, University of Tübingen.
- Ijaz Akhter, postdoctoral researcher, Australia Nationa University, Canbera.
- Silvia Zuffi, Research Scientist, IMATI-CNR, Institute for Applied Mathematics (Milano).
- Si Yong Yeo, Lecturer, Singapore University of Technology and Design.
- Cristina Garcia Cifuentes, Amazon.
- Chaohui Wang, Associate Professor, Laboratoire d'Informatique Gaspard Monge, Université Paris-Est, Paris, France.
- Søren Hauberg, Professor, Technical University of Denmark (DTU), Copenhagen.
- Hueihan Jhuang, industry, Taiwan.
- Javier Romero, Meta.
- Andreas Geiger, Professor, University of Tübingen
- Gregrory Shakhnarovich, Professor, Toyota Technological Institute at Chicago.
- Sung-Phil Kim, Associate Professor, School of Design and Human Engineering, UNIST, Korea.
- Ronan Fablet, Professor, Telecom Bretange.
How to reach me:
- email: black@tue.mpg.de
- Phone: +49 7071 601-1801
- FAX: +49 7071 601-1802
Mailing address
Michael J. Black
Max Planck Institute for Intelligent Systems
Max-Planck-Ring 4
72076 Tübingen
Germany
For more information including our address and directions, see the department CONTACT page.
I receive more email than I can read, let alone respond to. I apologize if you do not get a response. If you do not hear from me, consider the following:
- If you need something that is time sensitive (letter of reference, paper review, etc.), please contact or cc my assistant, ps-admin@tuebingen.mpg.de.
- If you have asked me to do something (like review a paper or grant proposal), and I haven't responded saying that I can do it, then I have not agreed to do it.
- If you are seeking a job or want to be a PhD student, visit the CAREER page
- Applications for jobs or graduate school should be sent to ps-apply@tuebingen.mpg.de
My assistant reads mail sent to me at black@is.mpg.de and black@tuebingen.mpg.de. If you have something particularly private, you can email me at black@cs.brown.edu and only I will read it. I do not check this often however.
Overview talks
A history of human motion in Computer Vision: From puppets to large language models,
CV 20/20 A Retrospective Vision, CVPR Workshops, June 2024 (pdf)
Towards the 3D Human Foundation Agent
Stanford SCIEN Colloquium, May 2024 (video)
Learning digital humans for the Metaverse
Keynote, 3DV 2021 (pptx, 654MB)
Towards putting realistic people in realistic scenes doing realistic things
TUM AI Lecture Series (YouTube)
Estimating 3D people interacting with 3D scenes
Various workshops at ICCV 2019 (pptx, 981MB)
Expressive human models for communication and interaction,
Various workshops at CVPR 2019 (pptx, 546MB)
Estimating Human Motion: Past, Present, and Future. (with full bibliography)
40 Years DAGM - Invited Talks, GCPR 2018 (pdf)
What is optical flow for? On prediction, persistence and structure.
Workshop on What is Optical Flow For? ECCV, Munich, Sept. 2018.
(ppt 76MB)
The Future and Generative Models: A Case Study of Human Bodies in Motion.
2-hour course given at the Int. Computer Vision Summer School, July 2016.
(ppt 1.5GB)
On building digital humans.
An overview of our work on 3D body shape, based on a series of talks during 2015.
(ppt 1GB)
Keynotes
Invited Conference, Workshop, and Summer School Talks
(youtube)
Invited Talks: Colloquia and Seminars
Other Talks
(incomplete list)
Scenes from Video (SfV)
- SfV1 2013, Barossa Valley, South Australia
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SfV2 2015 Colchagua Valley, Chile
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SfV3 2017 Lake Garda, Italy: http://sfv.is.tue.mpg.de/home
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SfV4 2019: Ribera del Duero, Spain