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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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25.01.2021

Richard Szeliski (University of Washington) will give a talk in the TUM AI lecture series on Jan 28th, 5pm! Livestream

10.12.2020

Frank Dellaert (Georgia Tech) will give a talk in the TUM AI lecture series on Dec 17th, 4pm! Livestream

15.10.2020

Jon Barron (Google) will give a talk in the TUM AI lecture series on Oct 22nd, 9pm! Livestream

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

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Dense Non-Rigid Shape Correspondence Using Random Forests (bibtex)
Dense Non-Rigid Shape Correspondence Using Random Forests (bibtex)
by E. Rodola, S. R Bulo, T. Windheuser, M. Vestner and D. Cremers
Reference:
Dense Non-Rigid Shape Correspondence Using Random Forests (E. Rodola, S. R Bulo, T. Windheuser, M. Vestner and D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. 
Bibtex Entry:
@string{cvpr="IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"}
@inproceedings{rodola-cvpr14,
 author = {E. Rodola and S. R Bulo and T. Windheuser and M. Vestner and D. Cremers},
 title = {Dense Non-Rigid Shape Correspondence Using Random Forests},
 booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
 year = {2014},
 titleurl = {randomforests.zip},
 topic = {Shape Analysis, Shape Matching, Machine Learning},
}
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Informatik IX
Chair of Computer Vision & Artificial Intelligence

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

Follow us on:
CVG Group DVL Group

News

25.01.2021

Richard Szeliski (University of Washington) will give a talk in the TUM AI lecture series on Jan 28th, 5pm! Livestream

10.12.2020

Frank Dellaert (Georgia Tech) will give a talk in the TUM AI lecture series on Dec 17th, 4pm! Livestream

15.10.2020

Jon Barron (Google) will give a talk in the TUM AI lecture series on Oct 22nd, 9pm! Livestream

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

More