Geometry Processing Award Programs
In order to feature some of the scientific highlights and breakthroughs in the field and to promote the reproducibility of research results, the Geometry Processing community has decided to give awards to authors of seminal papers and outstanding software projects.
SGP Software Award
On the occasion of the 10th edition of the Symposium on Geometry Processing in 2011, the SGP steering committee, in cooperation with the GeometryFactory as a sponsor, has established the SGP Software Award program. The intention of this award is to recognize researchers in the field who have contributed to the scientific progress in Geometry Processing by making their software available to the public such that others can reproduce the results and further build on them in their own research work. Eligible for the award are primarily open source projects and software libraries but also tools and applications. Nominations can be sent to email@example.com all year. The award is presented each year at the symposium.
The previous awardees are:
|2020||Wenzel Jakob, Marco Tarini, Daniele Panozzo, and Olga Sorkine-Hornung Instant Meshes|
We present a novel approach to remesh a surface into an isotropic triangular or quad-dominant mesh using a unified local smoothing operator that optimizes both the
edge orientations and vertex positions in the output mesh. Our algorithm produces meshes with high isotropy while naturally aligning and snapping edges to sharp
features. (project page, paper , github)
|2019||Rohan Sawhney and Keenan Crane Boundary First Flattening|
Boundary First Flattening (paper, github) is an application for surface parameterization.
BFF allows free-form editing of the flattened mesh, providing users direct control over the shape of the flattened domain.
The initial flattening is fully automatic, with distortion mathematically guaranteed to be as low or lower than any other conformal mapping tool.
BFF is highly optimized, allowing interactive editing of meshes with millions of triangles.
|2018||Tyson Brochu and Robert Bridson El Topo|
El Topo: Robust Topological Operations for Dynamic Explicit Surfaces (paper, github)
El Topo is a free C++ package for tracking dynamic surfaces represented as triangle meshes in 3D. It robustly handles topology changes such as merging and pinching off, while adaptively maintaining a tangle-free, high-quality triangulation.
|2017||Nicolas Mellado, Dror Aiger, Niloy J. Mitra Super4PCS|
Super4PCS (paper, github) is a set of C++ libraries, standalone applications and plugins released under the terms of the APACHE V2 licence, which makes it free for commercial and research use.
It provides state of the art global registration techniques for 3D pointclouds.
|2017||Paolo Cignoni, Guido Ranzuglia, Marco Callieri, Massimiliano Corsini, Matteo Dellepiane, Marco Di Benedetto, Fabio Ganovelli, Giorgio Marcias, Gianpaolo Palma, Nico Pietroni, Federico Ponchio, Luigi Malomo, Marco Tarini, Roberto Scopigno MeshLab|
MeshLab (http://www.meshlab.net/) is an open source, portable, and extensible system for the processing and editing of unstructured 3D triangular meshes. It also supports processing of raw data produced with 3D digitization tools/devices, providing a set of tools for editing, cleaning, healing, inspecting, rendering, texturing and converting this kind of models.
|2016||David Coeurjolly, Jacques-Olivier Lachaud, Bertrand Kerautret, Tristan Roussillon, Pierre Gueth, Jérémy Levallois, Isabelle Sivignon, Roland Denis, Kacper Pluta, Pablo Hernandez Cerdan
Digital Geometry focuses on the topology and geometry processing of digital structures (subsets of Z^d) with various applications in Pattern Recognition, Material Sciences or Medical Imaging. DGtal (http://dgtal.org) is a generic and collaborative C++ open source library for Digital Geometry programming whose main objective is to gather both cutting-edge and well-established developments from the digital geometry community.
|2015||Alec Jacobson, Daniele Panozzo, Christian Schêller, Olga Diamanti, Qingnan Zhou, Nico Pietroni, Stefan Bruggerr
, Kenshi Takayama, Wenzel Jakob, Nikolas De Giorgis, Luigi Rocca, Leonardo Sacht, Olga Sorkine-Hornung
Libigl is a C++ geometry processing library. It has a wide functionality including construction of sparse discrete differential geometry operators and finite-elements matrices such as the cotangent Laplacian and
diagonalized mass matrix, simple facet and edge-based topology data structures, mesh-viewing utilities for OpenGL and GLSL, and many core functions for matrix manipulation.
|2014||Marco Attene MeshFix|
Marco Attene is a researcher at the Institute of Applied Mathematics and Information Technologies of the CNR. He received his PhD from the University of Genoa where he was advised by Bianca Falcidieno and Michela Spagnuolo. His research focuses on problems in the domains of 3D geometric modelling, processing, and analysis.
Marco was awarded the SGP Software Award for release of the MeshFix code (http://sourceforge.net/projects/meshfix/) which robustly fixes small problems in meshes representing solid shapes ??? removing self-intersections, fixing non-manifold issues, filling holes, and returning a water-tight mesh.
|2013||Gael Guennebaud Eigen|
Gael Guennebaud is a research associate at INRIA Bordeaux Sud-Ouest. He received his PhD from the Research Institute for Computer Science of Toulouse where he was advised by Mathias Paulin. His research focuses on problems in the domains of point-based graphics, complex scenes, and soft-shadow rendering.
Gael was awarded the SGP Software Award for release of the Eigen code (http://eigen.tuxfamily.org/) which provides a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms.
|2012||Hang Si TetGen|
Hang Si is employed by Weierstrass Institute (WIAS) in Berlin. He received his PhD from the Institute of Mathematics of Technische Universitaet Berlin where he was advised by Gunter Ziegler. His research focuses on problems in the domain of automatic mesh generation.
Hang was awarded the SGP Software Award for release of the TetGen code (http://wias-berlin.de/software/tetgen/) which implements state-of-the-art methods for constructing Delaunay tetrahedralizations and quality tetrahedral meshes.
|2011||Misha Kazhdan Poisson Reconstruction|
Misha Kazhdan is an associate professor in the Computer Science Department at Johns Hopkins University. He received his PhD from Princeton University where he was advised by Thomas Funkhouser. His research focuses on problems in the domains of surface reconstruction, image-progress, and surface evolution.
Misha was awarded the SGP Software Award for release of the Poisson Surface Reconstruction code (http://www.cs.jhu.edu/~misha/Code/PoissonRecon/) which reconstructs manifold and water-tight surfaces from oriented point clouds.
Best Paper Awards
At each Symposium, up to three papers are recognized with a Best Paper Award. On this web-page we compile and maintain the list of previous award winners:
EGGS: Sparsity-Specific Code Generation
Xuan Tang, Teseo Schneider, Shoaib Kamil, Aurojit Panda, Jinyang Li and Daniele Panozzo
Best Student paper:
A Laplacian for Nonmanifold Triangle Meshes
Nicholas Sharp and Keenan Crane
Properties of Laplace Operators for Tetrahedral Meshes
Marc Alexa, Philipp Herholz, Max Kohlbrenner, and Olga Sorkine-Hornung
A Family of Barycentric Coordinates for Co-Dimension 1 Manifolds with Simplicial Facets
Zhipei Yan and Scott Schaefer
Hierarchical Functional Maps between Subdivision Surfaces
Meged Shoham, Amir Vaxman and Mirela Ben-Chen
A unified discrete framework for intrinsic and extrinsic Dirac operators for geometry processing
Zi Ye, Olga Diamanti, Chengcheng Tang, Tim Hoffmann and Leonidas Guibas
QuadFlow: A Scalable and Robust Method for Quadrangulation
Jingwei Huang, Yichao Zhou, Jonathan Shewchuk, Matthias Niessner, Leonidas Guibas
Sensor-aware Normal Estimation for Range Scan Point Clouds
Marc Comino Trinidad, Carlos Andujar, Pere Brunet, Antonio Chica
Modeling and Exploring Co-variations in the Geometry and Configuration of Man-made 3D Shape Families
Hamid Laga and Hedi Tabia
Spectral Affine-Kernel Embeddings
Max Budninskiy, Beibei Liu, Yiying Tong, Mathieu Desbrun
Isometry-Aware Preconditioning for Mesh Parameterization
Sebstian Claici, Mikhail Bessmeltsev, Scott Schaefer, Justin Solomon
Splines in the Space of Shells
Behrend Heeren, Martin Rumpf, Peter Schröder, Max Wardetzky, Benedikt Wirth
Or Litany, Emanuele Rodola, Alex M. Bronstein, Michael M. Bronstein, Daniel Cremers
Symmetry and Orbit Detection via Lie-Algebra Voting
Zeyun Shi, Pierre Alliez, Mathieu Desbrun, Hujun Bao, Jin Huang
Tight Relaxation of Quadratic Matching
Itay Kezurer, Shahar Z. Kovalsky, Ronen Basri, Yaron Lipman
Robust Articulated-ICP for Real-Time Hand Tracking
Andrea Tagliasacchi, Matthias Schröder, Anastasia Tkach, Sofien Bouaziz, Mario Botsch, Mark Pauly
Designing N-PolyVector Fields with Complex Polynomials
Olga Diamanti, Amir Vaxman, Daniele Panozzo, Olga Sorkine-Hornung
Super 4PCS: Fast Global Pointcloud Registration via Smart Indexing
Nicolas Mellado, Dror Aiger, Niloy Mitra
Consistent Shape Maps via Semidefinite Programming
Qixing Huang, Leonidas Guibas
Noise-Adaptive Shape Reconstruction from Raw Point Sets
Simon Giraudot, David Cohen-Steiner, Pierre Alliez
Practical Anisotropic Geodesy
Marcel Campen, Martin Heistermann, Leif Kobbelt
Computing Extremal Quasi-Conformal Maps
Ofir Weber, Denis Zorin, Ashish Myles
Modeling Polyhedral Meshes with Affine Maps
Stream Surface Parametrization by Flow-Orthogonal Front Lines
Maik Schulze, Tobias Germer, Christian Roessl, Holger Theisel
On approximation of the Laplace-Beltrami Operator and the Wilmore Energy of Surfaces
Klaus Hildebrandt, Konrad Polthier
A Complex View of Barycentric Mappings
Ofir Weber, Mirela Ben-Chen, Craig Gotsman, Kai Hormann
Multiscale Biharmonic Kernels
Raif M. Rustamov
Trivial Connections on Discrete Surfaces
Keenan Crane, Mathieu Desbrun, Peter Schröder
On Discrete Killing Vector Fields and Patterns on Surfaces
Mirela Ben-Chen, Adrian Butscher, Justin Solomon, Leonidas Guibas
Polygonal Boundary Evaluation of Minkowski Sums and Swept Volumes
Marcel Campen, Leif Kobbelt
A Concise and Provably Informative Multi-Scale Signature Based on Heat Diffusion
Jian Sun, Maks Ovsjanikov, Leonides Guibas
Rotating Scans for Systematic Error Removal
Fatemeh Abbasinejad, Yong J. Kil, Andrei Sharf, Nina Amenta
Estimating the Laplace-Beltrami Operator by Restricting 3D Functions
Ming Chuang, Linjie Luo, Benedict J. Brown, Szymon Rusinkiewicz, Michael Kazhdan
Surface sampling and the intrinsic Voronoi diagram
Ramsay Dyer, Hao Zhang, Torsten Möller
Polyhedral Finite Elements Using Harmonic Basis Functions (student paper)
Sebastian Martin, Peter Kaufmann, Mario Botsch, Martin Wicke, Markus Gross
Global Intrinsic Symmetries of Shapes (student paper)
Maks Ovsjanikov, Jian Sun, Leonidas Guibas
Voronoi-based Variational Reconstruction for Unoriented Point Sets
Pierre Alliez, David Cohen-Steiner, Yiying Tong, Mathieu Desbrun
PriMo: Coupled Prisms for Intuitive Surface Modeling
Mario Botsch, Mark Pauly, Markus Gross, Leif Kobbelt
This award is aimed to encourage and recognize the importance of the distribution of high-quality datasets on which geometry processing algorithms are tested.
Since 2016 it is given to authors of top-quality datasets and benchmarks provided to the comunity of Geometry Processing as testbed for present and future algorithms.
Angela Dai, Angel X. Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner
ScanNet is an RGB-D video dataset containing 2.5 million views in more than 1500 scans, annotated with 3D camera poses, surface reconstructions, and instance-level semantic segmentations.
ABC: A Big CAD Model Dataset For Geometric Deep Learning
Sebastian Koch, Albert Matveev, Zhongshi Jiang, Francis Williams, Alexey Artemov, Evgeny Burnaev, Marc Alexa, Denis Zorin, Daniele Panozzo
The ABC-Dataset (paper, data) is a collection of one million Computer-Aided Design (CAD) models for research of geometric deep learning methods and applications. Each model is a collection of explicitly parametrized curves and surfaces, providing ground truth for differential quantities, patch segmentation, geometric feature detection, and shape reconstruction.
ShapeNet: An ongoing effort to establish a richly-annotated, large-scale dataset of 3D shapes.
Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu
Thingi10k: A Dataset of 10,000 3D-Printing Models
Qingnan Zhou and Alec Jacobson
MPI FAUST Dataset: A data set containing 300 real, high-resolution human scans, with automatically computed ground-truth correspondences.
F. Bogo, J. Romero, M. Loper, and M. Black