License

Software Copyright License for non-commercial scientific research purposes

Please read carefully the following terms and conditions and any accompanying documentation before you download and/or use the Stitched Puppet Software/Data, (the "Software"). By downloading and/or using the Software, you acknowledge that you have read these terms and conditions, understand them, and agree to be bound by them. If you do not agree with these terms and conditions, you must not download and/or use the Software. Any infringement of the terms of this agreement will automatically terminate your rights under this License

 

Ownership

The Software and the associated materials has been developed at the 

Max Planck Institute for Intelligent Systems (hereinafter "MPI") and the Max Planck Institute for Biological Cybernetics (hereinafter “KYB”).

Any copyright or patent right is owned by and proprietary material of the

Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (hereinafter “MPG”; MPI and MPG hereinafter collectively “Max-Planck”)

hereinafter the “Licensor”.

 

License Grant

Licensor grants you (Licensee) personally a single-user, non-exclusive, non-transferable, free of charge right:

  • To install the Software on computers owned, leased or otherwise controlled by you and/or your organization;
  • To use the Software for the sole purpose of performing non-commercial scientific research, non-commercial education, or non-commercial artistic projects;
  • To modify, adapt, translate or create derivative works based upon the Software.

Any other use, in particular any use for commercial purposes, is prohibited. This includes, without limitation, incorporation in a commercial product, use in a commercial service, or production of other artefacts for commercial purposes. The Software may not be reproduced, modified and/or made available in any form to any third party without Max-Planck’s prior written permission. 

The Software may not be used for pornographic purposes or to generate pornographic material whether commercial or not. This license also prohibits the use of the Software to train methods/algorithms/neural networks/etc. for commercial use of any kind. By downloading the Software, you agree not to reverse engineer it.

 

No Distribution

The Software and the license herein granted shall not be copied, shared, distributed, re-sold, offered for re-sale, transferred or sub-licensed in whole or in part except that you may make one copy for archive purposes only.

 

Disclaimer of Representations and Warranties

You expressly acknowledge and agree that the Software results from basic research, is provided “AS IS”, may contain errors, and that any use of the Software is at your sole risk. LICENSOR MAKES NO REPRESENTATIONS OR WARRANTIES OF ANY KIND CONCERNING THE SOFTWARE, NEITHER EXPRESS NOR IMPLIED, AND THE ABSENCE OF ANY LEGAL OR ACTUAL DEFECTS, WHETHER DISCOVERABLE OR NOT. Specifically, and not to limit the foregoing, licensor makes no representations or warranties (i) regarding the merchantability or fitness for a particular purpose of the Software, (ii) that the use of the Software will not infringe any patents, copyrights or other intellectual property rights of a third party, and (iii) that the use of the Software will not cause any damage of any kind to you or a third party.

 

Limitation of Liability

Because this Software License Agreement qualifies as a donation, according to Section 521 of the German Civil Code (Bürgerliches Gesetzbuch – BGB) Licensor as a donor is liable for intent and gross negligence only. If the Licensor fraudulently conceals a legal or material defect, they are obliged to compensate the Licensee for the resulting damage.
Licensor shall be liable for loss of data only up to the amount of typical recovery costs which would have arisen had proper and regular data backup measures been taken. For the avoidance of doubt Licensor shall be liable in accordance with the German Product Liability Act in the event of product liability. The foregoing applies also to Licensor’s legal representatives or assistants in performance. Any further liability shall be excluded.
Patent claims generated through the usage of the Software cannot be directed towards the copyright holders.
The Software is provided in the state of development the licensor defines. If modified or extended by Licensee, the Licensor makes no claims about the fitness of the Software and is not responsible for any problems such modifications cause.

 

No Maintenance Services

You understand and agree that Max-Planck is under no obligation to provide either maintenance services, update services, notices of latent defects, or corrections of defects with regard to the Data. Max-Planck nevertheless reserves the right to update, modify, or discontinue the Data at any time.

 

Publications using the Software

You acknowledge that the Software is a valuable scientific resource and agree to appropriately reference the following paper in any publication making use of the Software.

 

Citation:

@inproceedings{Zuffi:CVPR:2015,
  title = {The Stitched Puppet: A Graphical Model of {3D} Human Shape and Pose},
  author = {Zuffi, Silvia and Black, Michael J.},
  booktitle = { IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2015},
  month = jun,
  abstract = {We propose a new 3D model of the human body that is both realistic and part-based. The body is represented by
  a graphical model in which nodes of the graph correspond to body parts that can independently translate and rotate
  in 3D as well as deform to capture pose-dependent shape variations. Pairwise potentials define a “stitching cost” for
  pulling the limbs apart, giving rise to the stitched puppet model (SPM). Unlike existing realistic 3D body models, the
  distributed representation facilitates inference by allowing the model to more effectively explore the space of poses,
  much like existing 2D pictorial structures models. We infer pose and body shape using a form of particle-based max-product belief propagation. This gives the SPM the realism of recent 3D body models with the computational advantages
  of part-based models. We apply the SPM to two challenging problems involving estimating human shape and
  pose from 3D data. The first is the FAUST mesh alignment challenge (http://faust.is.tue.mpg.de/), where ours is the first method to successfully align all 3D meshes. The second involves estimating pose and shape from crude visual hull representations of complex
  body movements.},
  year = {2015}
}

and

Pacheco, J., Zuffi, S., Black, M.J. and Sudderth, E.
Proceedings of the 31st International Conference on Machine Learning (ICML-14), J. Machine Learning Research Workshop and Conf. and Proc.,
Vol. 32, pages 1152-1160, Beijing, China. June 2014.

 

Commercial licensing opportunities

For commercial uses of the Software, please send email to ps-license@tue.mpg.de

This Agreement shall be governed by the laws of the Federal Republic of Germany except for the UN Sales Convention.

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