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The Graphics Replicability Stamp Initiative (GRSI) is an independent group of volunteers who help the community by enabling sharing of code and data as a community resource for non-commercial use. The volunteers check the submitted code and certify its replicability, awarding a replicability stamp, which is an additional recognition for authors of accepted papers who are willing to provide a complete implementation of their algorithm, to replicate the results presented in their paper. The replicability stamp is not meant to be a measure of the scientific quality of the paper or of the usefulness of presented algorithms. Rather, it is meant to be an endorsement of the replicability of the results presented in the paper and the recognition of the service provided to the community by releasing the code. Submissions for the replicability stamp will be considered only *after* the paper has been fully accepted. Submissions that are awarded the replicability stamp will receive additional exposure by being listed on this website. The purpose of this stamp is to promote reproducibility of research results and to allow scientists and practitioners to immediately benefit from state-of-the-art research results, without spending months re-implementing the proposed algorithms and trying to find the right parameter values. We also hope that it will indirectly foster scientific progress, since it will allow researchers to reliably compare with and to build upon existing techniques, knowing that they are using exactly the same implementation. This is an initiative supported by a growing list of publishers, journals and conferences.

baacloud加速器官方网址-outline

Any paper accepted in or after 2017 at one the following journals is eligible to apply for the stamp:
  • ACM Transaction on Graphics
  • IEEE Transaction on Visualization and Computer Graphics
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  • Elsevier Computers & Graphics
  • Elsevier Computer Aided Geometric Design
  • Elsevier Computer-Aided Design
The application process is lightweight. You will have to provide general information on the submission, a representative image, a link to a public git repository with the source code, and instructions on how to compile and replicate the results. The code should compile on a vanilla installation of one of the major operating systems (Linux, MacOSX, or Windows), have a license that allows non-commercial usage, and only depend on libraries that are free for academic or research purposes. The code quality will not be evaluated, the purpose of the stamp is only to simplify replicability of the results: in its simplest form, the code should reproduce the data used to generate one result figure shown in the paper.

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baacloud加速器官方网址-outline

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Bart Iver van Blokland, Theoharis Theoharis
Elsevier Computers & Graphics (C&G)

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Jan Bender, Tassilo Kugelstadt, Marcel Weiler, Dan Koschier
IEEE Transactions on Visualization and Computer Graphics (TVCG)

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Interactive Visual Exploration of Metabolite Ratios in MR Spectroscopy Studies

Laura Garrison, Jakub Vasicek, Alexander R. Craven, Renate Gruner, Noeska N. Smit, Stefan Bruckner
Elsevier Computers & Graphics (C&G)

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IEEE Transactions on Visualization and Computer Graphics (TVCG)

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Vectorization of persistence barcode with applications in pattern classification of porous structures

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Elsevier Computers & Graphics (C&G)

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Surfel-Based Incremental Reconstruction of the Boundary between Known and Unknown Space

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IEEE Transactions on Visualization and Computer Graphics (TVCG)

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Elsevier Computers & Graphics (C&G)

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baacloud加速器官方网址-outline

The Replicability committee is a independent group of volunteers from the graphics community who want to help the community by enabling sharing of code and data as a community resource for non-commercial use.

General Chair

Marco Attene (CNR - IMATI)

Associate Chairs

Marc Alexa (TU Berlin) - ACM TOG,
Klaus Mueller (Stony Brook University) - IEEE TVCG,
Helwig Hauser (University of Bergen) - Wiley CGF,
Joaquim Jorge (Instituto Superior Tecnico Lisboa) - Elsevier C&G,
Konrad Polthier (FU Berlin) - Elsevier CAGD
Vadim Shapiro (Univ. Wisconsin-Madison) - Elsevier CAD

Advisory Board

Daniele Panozzo (New York Univ.), Leif Kobbelt (RWTH Aachen), Holly Rushmeier (Yale Univ.), Wenzel Jakob (EPFL), Sylvain Paris (Adobe Research), Kun Zhou (Zhejiang Univ.), Juliana Freire (New York Univ.), Kavita Bala (Cornell), Leila De Floriani (Univ. of Maryland), Min Chen (Univ. of Oxford), David Coeurjolly (CNRS).

Program Committee

Alec Jacobson (University of Toronto), Carlos Scheidegger (University of Arizona), Christoph Garth (University of Kaiserslautern), David Bommes (University of Bern), David Coeurjolly (CNRS), Dmitriy Smirnov (MIT), Dmitry Sokolov (INRIA), Dobrina Boltcheva (University of Lorraine), Francis Williams (NYU), James Zhou (Adobe Research), Jeremie Dumas (NYU), Julian Panetta (EPFL), Julie Digne (CNRS), Julien Tierny (CNRS), Jun-Yan Zhu (MIT), Justin Solomon (MIT), Kenshi Takayama (NII), Marcel Campen (Osnabruck University), Marco Livesu (IMATI), Mario Botsch (University of Bielefeld), Miika Aittala (MIT), Nico Pietroni (ISTI CNR), Nicolas Bonneel (CNRS), Nicolas Mellado (CNRS), Noam Aigerman (ETHZ), Olga Diamanti (TU Berlin), Oliver Glauser (ETHZ), Roi Poranne (ETHZ), Ryan Schmidt (Autodesk), Sebastian Koch (TU Berlin), Shahar Kovalsky (Duke University), Srinath Sridhar (Stanford), Teseo Schneider (NYU), Vijay Natarajan (Indian Institute of Science), Vladimir Kim (Adobe Research), Xifeng Gao (NYU), Yotam Gingold (George Mason University), Yu Wang (MIT), Zhongshi Jiang (NYU).

Technical Manager

Daniela Cabiddu (CNR - IMATI)

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