The Mission

The Graphics Replicability Stamp Initiative (GRSI) is an independent group of volunteers who want to help the community by enabling sharing of code and data as a community resource for non-commercial use. The volunteers review 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 algo-rithms. 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.

Application Process

Any paper accepted in 2017 at one the following journals is eligible to apply for the stamp:
  • ACM Transaction on Graphics
  • Elsevier Computer & Graphics
  • Elsevier Computer Aided Geometric Design
The application process is lightweight, please refer to the website of the journals for their application form. 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 every result figure shown in the paper.

Replicable Papers

Interpolations of Smoke and Liquid Simulations

Nils Thuerey
ACM Transactions on Graphics (TOG)

Repository

Disjoint Convex Shell and its Applications in Mesh Unfolding

Yun-hyeong Kim, Zhonghua Xi, Jyh-Ming Lien
Symposium on Solid & Physical Modeling 2017

Repository

Hole Detection of a Planar Point Set: An Empty Disk Approach

​​Subhasree Methirumangalath, Shyam Sundar Kannan, Amal Dev Parakkat, and Ramanathan Muthuganapathy
Shape Modeling International 2017

Repository

Improved shape for refinable surfaces with singularly parameterized irregularities

Kestutis Karciauskas, Jorg Peters
Symposium on Solid & Physical Modeling 2017

Repository

Extrinsically Smooth Direction Fields

Zhiyang Huang, Tao Ju
Shape Modeling International 2016

Repository

PinMesh -- Fast and Exact 3D Point Location Queries using a Uniform Grid

Salles V.G. Magalhães, Marcus V.A. Andrade, W. Randolph Franklin, Wenli Li
Shape Modeling International 2016

Repository

The 2D Shape Structure Dataset: A user annotated open Access Database

Axel Carlier, Kathryn Leonard, Stefanie Hahmann, Geraldine Morin, Misha Collins
Shape Modeling International 2016

Repository

Computing a Discrete Morse Gradient From a Watershed Decomposition

Lidija Comic, Leila De Floriani, Federico Iuricich, Paola Magillo
Shape Modeling International 2016

Repository

A Closed-Form Formulation of HRBF-Based Surface Reconstruction by Approximate Solution

Shengjun Liu, Charlie C.L. Wang, Guido Brunnett, Jun Wang
Symposium on Solid & Physical Modeling 2016

Repository

Modeling and Analysis of Origami Structures with Smooth Folds

Edwin A. Peraza Hernandez, Darren J. Hartl, Ergun Akleman, Dimitris C. Lagoudas
Symposium on Solid & Physical Modeling 2016

Repository

Planar Minimization Diagrams via Subdivision with Applications to Anisotropic Voronoi Diagrams

Huck Bennett, Evanthia Papadopoulou, Chee Yap
Symposium of Geometry Processing 2016

Repository

Crawl through Neighbors: A Simple Curve Reconstruction Algorithm

Amal Dev Parakkat, Ramanathan Muthuganapathy
Symposium of Geometry Processing 2016

Repository

Non-Rigid Puzzles

Or Litany, Emanuele Rodola, Alex Bronstein, Michael Bronstein, Daniel Cremers
Symposium of Geometry Processing 2016

Repository

Construction of Topologically Correct and Manifold Isosurfaces

Roberto Grosso
Symposium of Geometry Processing 2016

Repository

Curve Reconstruction with Many Fewer Samples

Stefan Ohrhallinger, Scott Mitchell, Michael Wimmer
Symposium of Geometry Processing 2016

Repository

Complex Transfinite Barycentric Mappings with Similarity Kernels

Renjie Chen, Craig Gotsman
Symposium of Geometry Processing 2016

Repository

Organization

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

Daniele Panozzo (New York University)

Associate Chairs

Kavita Bala (Cornell) - ACM,
Joaquim Jorge (Instituto Superior Tecnico Lisboa) - C&G,
Konrad Polthier (FU Berlin) - CAGD

Conference Chairs

Marco Attene (IMATI-GE / CNR) - SMI 2017,
Mario Botsch (University of Bielefeld) - SPM 2017,

Advisory Board

Leif Kobbelt (RWTH Aachen), Holly Rushmeier (Yale University), Wenzel Jakob (EPFL), Sylvain Paris (Adobe Research), Kun Zhou (Zhejiang University), Juliana Freire (New York University).

Program Committee

Alec Jacobson (University of Toronto), David Bommes, (RWTH Aachen University), Justin Solomon (MIT), Kenshi Takayama (NII), Nico Pietroni (CNR Pisa), Ryan Schmidt (Autodesk), Shahar Kovalsky (Yale University), Vladimir Kim (Adobe), Yotam Gingold (George Mason University), Julian Panetta (EPFL), Oliver Glauser (ETHZ), Christian Schuller (ETHZ), Sebastian Koch (TU Berlin), Noam Aigerman (ETHZ), Dmitry Sokolov (INRIA), Jeremie Dumas (NYU), Qingnan Zhou (Adobe), Chengcheng Tang (Stanford University), Xifeng Gao (NYU), Mario Botsch (University of Bielefeld), Julien Tierny (CNRS), Miika Aittala (Aalto University), Roi Poranne (ETHZ).