Lifting Methods for Global Matching Problems

Informazioni relative al progetto

LiftMatch

ID dell’accordo di sovvenzione: 771136

DOI

10.3030/771136

Progetto concluso il 7 Febbraio 2023

Data della firma CE 12 Febbraio 2018

Data di avvio 1 Marzo 2018

Data di completamento 28 Febbraio 2023

Finanziato da

• EXCELLENT SCIENCE - European Research Council (ERC)

Costo totale

€ 1 675 640,00

Contributo UE

€ 1 675 640,00

Coordinato da

WEIZMANN INSTITUTE OF SCIENCE
Israel

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Pubblicazioni

Conference proceedings (13)

Sal: Sign agnostic learning of shapes from raw data

Autori: M Atzmon, Y Lipman
Pubblicato in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020., 2020
Editore: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020.

Frame Averaging for Invariant and Equivariant Network Design

Autori: Omri Puny, Matan Atzmon, Heli Ben-Hamu, Ishan Misra, Aditya Grover, Edward J. Smith, Yaron Lipman
Pubblicato in: 2022
Editore: International Conference on Learning Representations

Controlling neural level sets

Autori: M Atzmon, N Haim, L Yariv, O Israelov, H Maron, Y Lipman
Pubblicato in: Advances in Neural Information Processing Systems (NeurIPS), 2019
Editore: Advances in Neural Information Processing Systems (NeurIPS)

Set2Graph: Learning Graphs From Sets

Autori: Hadar Serviansky, Nimrod Segol, Jonathan Shlomi, Kyle Cranmer, Eilam Gross, Haggai Maron, Yaron Lipman
Pubblicato in: 2020
Editore: 34th Annual Conference on Neural Information Processing Systems (NeurIPS)

Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance

Autori: Lior Yariv, Yoni Kasten, Dror Moran, Meirav Galun, Matan Atzmon, Ronen Basri, Yaron Lip- man
Pubblicato in: 2020
Editore: 34th Annual Conference on Neural Information Processing Systems (NeurIPS)

Provably powerful graph networks

Autori: H Maron, H Ben-Hamu, H Serviansky, Y Lipman
Pubblicato in: Advances in Neural Information Processing Systems (NeurIPS), 2019
Editore: Advances in Neural Information Processing Systems (NeurIPS)

(Probably) concave graph matching

Autori: Haggai Maron, Yaron Lipman
Pubblicato in: Advances in Neural Information Processing Systems, 2018, Pagina/e 408--418
Editore: Advances in Neural Information Processing Systems

Invariant and Equivariant Graph Networks

Autori: Haggai Maron and Heli Ben{-}Hamu and Nadav Shamir and Yaron Lipman
Pubblicato in: 7th International Conference on Learning Representations, {ICLR} 2019, New Orleans, LA, USA, May 6-9, 2019, 2019
Editore: 7th International Conference on Learning Representations, {ICLR} 2019, New Orleans, LA, USA, May 6-9, 2019

Surface Networks via General Covers

Autori: Niv Haim*, Nimrod Segol*, Heli Ben-Hamu, Haggai Maron, Yaron Lipman
Pubblicato in: International Conference on Computer Vision (ICCV) 2019, 2019
Editore: International Conference on Computer Vision (ICCV)

On the Universality of Invariant Networks

Autori: Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman
Pubblicato in: International Conference on Machine Learning (ICML) 2019, 2019
Editore: International Conference on Machine Learning (ICML)

Implicit Geometric Regularization for Learning Shapes

Autori: Gropp, Amos; Yariv, Lior; Haim, Niv; Atzmon, Matan; Lipman, Yaron
Pubblicato in: Thirty-seventh International Conference on Machine Learning (ICML), Numero 1, 2020
Editore: Thirty-seventh International Conference on Machine Learning (ICML)

Moser Flow: Divergence-based Generative Modeling on Manifolds

Autori: Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman
Pubblicato in: 2021
Editore: Neural Information Processing Systems (NeurIPS)

On universal equivariant set networks

Autori: N Segol, Y Lipman
Pubblicato in: International Conference on Learning Representations (ICLR) 2020, 2020
Editore: International Conference on Learning Representations (ICLR)

Peer reviewed articles (6)

Robust optimization for topological surface reconstruction

Autori: Roee Lazar, Nadav Dym, Yam Kushinsky, Zhiyang Huang, Tao Ju, Yaron Lipman
Pubblicato in: ACM Transactions on Graphics, Numero 37/4, 2018, Pagina/e 1-10, ISSN 0730-0301
Editore: Association for Computing Machinary, Inc.
DOI: 10.1145/3197517.3201348

Linear variational principle for Riemann mappings and discrete conformality

Autori: Nadav Dym, Raz Slutsky, Yaron Lipman
Pubblicato in: Proceedings of the National Academy of Sciences, Numero 116/3, 2019, Pagina/e 732-737, ISSN 0027-8424
Editore: National Academy of Sciences
DOI: 10.1073/pnas.1809731116

Multi-chart generative surface modeling

Autori: Heli Ben-Hamu, Haggai Maron, Itay Kezurer, Gal Avineri, Yaron Lipman
Pubblicato in: ACM Transactions on Graphics, Numero 37/6, 2019, Pagina/e 1-15, ISSN 0730-0301
Editore: Association for Computing Machinary, Inc.
DOI: 10.1145/3272127.3275052

Point convolutional neural networks by extension operators

Autori: Matan Atzmon, Haggai Maron, Yaron Lipman
Pubblicato in: ACM Transactions on Graphics, Numero 37/4, 2018, Pagina/e 1-12, ISSN 0730-0301
Editore: Association for Computing Machinary, Inc.
DOI: 10.1145/3197517.3201301

Sinkhorn Algorithm for Lifted Assignment Problems

Autori: Yam Kushinsky, Haggai Maron, Nadav Dym, Yaron Lipman
Pubblicato in: SIAM Journal on Imaging Sciences, Numero 12/2, 2019, Pagina/e 716-735, ISSN 1936-4954
Editore: Society for Industrial and Applied Mathematics
DOI: 10.1137/18m1196480

Exact Recovery with Symmetries for the Doubly Stochastic Relaxation

Autori: Nadav Dym
Pubblicato in: SIAM Journal on Applied Algebra and Geometry, Numero 2/3, 2018, Pagina/e 462-488, ISSN 2470-6566
Editore: SIAM
DOI: 10.1137/17m1132264