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Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich



Photometry-Based Reconstruction

We are concerned with the reconstruction of the 3D world based on the interaction between shape, illumination and material. RGB images provide observations from which we can infer the above, by solving an ill-posed inverse rendering problem. This enables reconstructions with high-frequency geometric information and meaningful albedo estimates, allowing for plausible rendering under novel lighting conditions. We are especially interested in Shape-from-Shading and Photometric Stereo, where the former tries to infer geometry, lighting and appearance from a single image, and the latter attempts to estimate the same desired scene properties from multiple images and different illumination.

Keyword: photometry


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Conference and Workshop Papers
[]Recovering Real-world Reflectance Properties and Shading from HDR Imagery (B. Haefner, S. Green, A. Oursland, D. Andersen, M. Goesele, D. Cremers, R. Newcombe and T. Whelan), In International Conference on 3D Vision (3DV), 2021. ([paper] [supp] [FB Research] [video]) [bibtex]
Book Chapters
[] On the Well-Posedness of Uncalibrated Photometric Stereo Under General Lighting (M Brahimi, Y Quéau, B Haefner and D Cremers), Chapter in Advances in Photometric 3D-Reconstruction (JD Durou, M Falcone, Y Quéau, S Tozza, eds.), Springer International Publishing, 2020.  [bibtex] [pdf] [doi] [pdf]
Journal Articles
[]Photometric Depth Super-Resolution (B. Haefner, S. Peng, A. Verma, Y. Quéau and D. Cremers), In IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 42, 2020. ([supp] [project page] [ieeexplore]) [bibtex] [arXiv:1809.10097] [pdf]
Conference and Workshop Papers
[]Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach (L. Sang, B. Haefner and D. Cremers), In IEEE Winter Conference on Applications of Computer Vision (WACV), 2020. ([poster] [presentation] [code] [cvf]) [bibtex] [arXiv:1912.06501] [pdf]Spotlight Presentation
Conference and Workshop Papers
[]Variational Uncalibrated Photometric Stereo under General Lighting (B. Haefner, Z. Ye, M. Gao, T. Wu, Y. Quéau and D. Cremers), In International Conference on Computer Vision (ICCV), 2019. ([supp] [poster] [code] [cvf] [ieeexplore]) [bibtex] [arXiv:1904.03942] [pdf]
[]Photometric Segmentation: Simultaneous Photometric Stereo and Masking (B. Haefner, Y. Quéau and D. Cremers), In International Conference on 3D Vision (3DV), 2019. ([poster] [ieeexplore]) [bibtex] [pdf]Spotlight Presentation
Conference and Workshop Papers
[]Fight ill-posedness with ill-posedness: Single-shot variational depth super-resolution from shading (B. Haefner, Y. Quéau, T. Möllenhoff and D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. ([supp] [poster] [code] [cvf] [video]) [bibtex] [pdf] [video]Spotlight Presentation
Conference and Workshop Papers
[]Depth Super-Resolution Meets Uncalibrated Photometric Stereo (S. Peng, B. Haefner, Y. Quéau and D. Cremers), In International Conference on Computer Vision Workshops (ICCVW), 2017. ([code] [cvf]) [bibtex] [arXiv:1708.00411] [pdf]Oral Presentation at ICCV Workshop on Color and Photometry in Computer Vision
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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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In April 2022 Jürgen Sturm, Christian Kerl and Daniel Cremers were featured among the top 10 most influential scholars in robotics of the last decade.


We have open PhD and postdoc positions! To apply, please use our application form.


We have six papers accepted to CVPR 2022 in New Orleans!


We have two papers accepted to ICRA 2022 - congrats to Lukas von Stumberg, Qing Cheng and Niclas Zeller!