Michael J. Black
Impact in
- Computer Vision and Pattern Recognition top 0.01%
- Human Pose and Action Recognition
- Advanced Vision and Imaging
- Video Surveillance and Tracking Methods
- Advanced Image Processing Techniques
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- Computer Graphics and Visualization Techniques
Papers in
-
- Human Pose and Action Recognition 106
- Advanced Vision and Imaging 65
- Video Surveillance and Tracking Methods 32
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- 3D Shape Modeling and Analysis 75
- Co-authors
- P. Anandan (3 shared papers)Gerard Pons‐Moll (9 shared papers)Javier Romero (6 shared papers)Matthew Loper (8 shared papers)Leonid Sigal (11 shared papers)Naureen Mahmood (10 shared papers)Deqing Sun (6 shared papers)Stefan Roth (5 shared papers)
- Journals
- ACM Transactions on Graphics (17 papers)International Journal of Computer Vision (7 papers)Journal of Vision (5 papers)Journal of Neural Engineering (4 papers)Journal of Neuroscience (3 papers)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Michael J. Black
252 papers receiving 23.7k citations
Michael J. Black's Hit Papers
Peers
Comparison fields: 5 of 185
- Computer Vision and Pattern Recognition 18.2k
- Computer Graphics and Computer-Aided Design 2.5k
- Human-Computer Interaction 2.1k
- Computational Mechanics 6.7k
- Control and Systems Engineering 3.7k
Countries citing papers authored by Michael J. Black
This map shows the geographic impact of Michael J. Black's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael J. Black with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael J. Black more than expected).
Fields of papers citing papers by Michael J. Black
This network shows the impact of papers produced by Michael J. Black. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael J. Black. The network helps show where Michael J. Black may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael J. Black, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 266 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | SMPL Hit paper breakdown → | 2015 | 2149 |
| 2 | The Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow Fields Hit paper breakdown → | 1996 | 1115 |
| 3 | End-to-End Recovery of Human Shape and Pose Hit paper breakdown → | 2018 | 1074 |
| 4 | Secrets of optical flow estimation and their principles Hit paper breakdown → | 2010 | 985 |
| 5 | Robust anisotropic diffusion Hit paper breakdown → | 1998 | 913 |
| 6 | Optical Flow Estimation Using a Spatial Pyramid Network Hit paper breakdown → | 2017 | 819 |
| 7 | HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human Motion Hit paper breakdown → | 2009 | 731 |
| 8 | Learning a model of facial shape and expression from 4D scans Hit paper breakdown → | 2017 | 633 |
| 9 | Embodied hands Hit paper breakdown → | 2017 | 595 |
| 10 | On the unification of line processes, outlier rejection, and robust statistics with applications in early vision Hit paper breakdown → | 1996 | 508 |
| 11 | A Quantitative Analysis of Current Practices in Optical Flow Estimation and the Principles Behind Them Hit paper breakdown → | 2013 | 423 |
| 12 | FAUST: Dataset and Evaluation for 3D Mesh Registration Hit paper breakdown → | 2014 | 408 |
| 13 | Learning an animatable detailed 3D face model from in-the-wild images Hit paper breakdown → | 2021 | 354 |
| 14 | 2011 | 354 | |
| 15 | 1997 | 322 | |
| 16 | 2005 | 313 | |
| 17 | Unite the People: Closing the Loop Between 3D and 2D Human Representations Hit paper breakdown → | 2017 | 298 |
| 18 | 2008 | 294 | |
| 19 | ClothCap Hit paper breakdown → | 2017 | 293 |
| 20 | Action-Conditioned 3D Human Motion Synthesis with Transformer VAE Hit paper breakdown → | 2021 | 281 |
About Michael J. Black
Michael J. Black is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Control and Systems Engineering, Cognitive Neuroscience and Biomedical Engineering, having authored 266 papers that have together received 24.8k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (106 papers), 3D Shape Modeling and Analysis (75 papers), Advanced Vision and Imaging (65 papers), Human Motion and Animation (39 papers), Video Surveillance and Tracking Methods (32 papers), EEG and Brain-Computer Interfaces (28 papers), Neuroscience and Neural Engineering (25 papers) and Computer Graphics and Visualization Techniques (25 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (18.2k citations), Computer Graphics and Computer-Aided Design (2.5k citations), Human-Computer Interaction (2.1k citations), Computational Mechanics (6.7k citations) and Control and Systems Engineering (3.7k citations). Michael J. Black has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include P. Anandan, Gerard Pons‐Moll, Javier Romero, Matthew Loper, Leonid Sigal, Naureen Mahmood, Deqing Sun, Stefan Roth, Anurag Ranjan and Javier Romero. Their work appears in journals such as ACM Transactions on Graphics, International Journal of Computer Vision, Journal of Vision, Journal of Neural Engineering and Journal of Neuroscience.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.