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ORCIDMaks Ovsjanikov
Maksim Ovsjanikov
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- affiliation: École polytechnique, Paris, France
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2020 – today
- 2024
[j58]Jarne Van den Herrewegen
, Tom Tourwé, Maks Ovsjanikov, Francis Wyffels:
Fine-tuning 3D foundation models for geometric object retrieval. Comput. Graph. 122: 103993 (2024)- [j57]Ramana Sundararaman, Nicolas Donati, Simone Melzi, Etienne Corman, Maks Ovsjanikov:
Deformation Recovery: Localized Learning for Detail-Preserving Deformations. ACM Trans. Graph. 43(6): 219:1-219:16 (2024) - [c70]Mariem Mezghanni, Malika Boulkenafed, Maks Ovsjanikov:
RIVQ-VAE: Discrete Rotation-Invariant 3D Representation Learning. 3DV 2024: 1382-1391 - [c69]Sara Hahner, Souhaib Attaiki, Jochen Garcke, Maks Ovsjanikov:
Unsupervised Representation Learning for Diverse Deformable Shape Collections. 3DV 2024: 1594-1604 - [c68]Nissim Maruani, Maks Ovsjanikov, Pierre Alliez, Mathieu Desbrun:
PoNQ: A Neural QEM-Based Mesh Representation. CVPR 2024: 3647-3657 - [c67]Robin Magnet, Maks Ovsjanikov:
Memory-Scalable and Simplified Functional Map Learning. CVPR 2024: 4041-4050 - [c66]Thomas Wimmer, Peter Wonka, Maks Ovsjanikov:
Back to 3D: Few-Shot 3D Keypoint Detection with Back-Projected 2D Features. CVPR 2024: 4154-4164 - [c65]Ramana Sundararaman, Roman Klokov, Maks Ovsjanikov:
Self-Supervised Dual Contouring. CVPR 2024: 4681-4691 - [c64]Souhail Hadgi, Lei Li, Maks Ovsjanikov:
To Supervise or Not to Supervise: Understanding and Addressing the Key Challenges of Point Cloud Transfer Learning. ECCV (78) 2024: 146-163 - [i67]Maysam Behmanesh, Maks Ovsjanikov:
Smoothed Graph Contrastive Learning via Seamless Proximity Integration. CoRR abs/2402.15270 (2024) - [i66]Souhaib Attaiki, Maks Ovsjanikov:
Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction. CoRR abs/2403.06804 (2024) - [i65]Nissim Maruani, Maks Ovsjanikov, Pierre Alliez, Mathieu Desbrun:
PoNQ: a Neural QEM-based Mesh Representation. CoRR abs/2403.12870 (2024) - [i64]Souhail Hadgi, Lei Li, Maks Ovsjanikov:
To Supervise or Not to Supervise: Understanding and Addressing the Key Challenges of 3D Transfer Learning. CoRR abs/2403.17869 (2024) - [i63]Robin Magnet, Maks Ovsjanikov:
Memory-Scalable and Simplified Functional Map Learning. CoRR abs/2404.00330 (2024) - [i62]Ramana Sundararaman, Roman Klokov, Maks Ovsjanikov:
Self-Supervised Dual Contouring. CoRR abs/2405.18131 (2024) - [i61]Léopold Maillard, Nicolas Sereyjol-Garros, Tom Durand, Maks Ovsjanikov:
DeBaRA: Denoising-Based 3D Room Arrangement Generation. CoRR abs/2409.18336 (2024) - [i60]Ramana Sundararaman, Nicolas Donati, Simone Melzi, Etienne Corman, Maks Ovsjanikov:
Deformation Recovery: Localized Learning for Detail-Preserving Deformations. CoRR abs/2410.08225 (2024) - 2023
- [j56]Robin Magnet, Maks Ovsjanikov:
Scalable and Efficient Functional Map Computations on Dense Meshes. Comput. Graph. Forum 42(2): 89-101 (2023) - [j55]Lei Li, Hongbo Fu, Maks Ovsjanikov:
WSDesc: Weakly Supervised 3D Local Descriptor Learning for Point Cloud Registration. IEEE Trans. Vis. Comput. Graph. 29(7): 3368-3379 (2023) - [c63]Souhaib Attaiki, Maks Ovsjanikov:
Understanding and Improving Features Learned in Deep Functional Maps. CVPR 2023: 1316-1326 - [c62]Panos Achlioptas, Maks Ovsjanikov, Leonidas J. Guibas, Sergey Tulyakov:
Affection: Learning Affective Explanations for Real-World Visual Data. CVPR 2023: 6641-6651 - [c61]Souhaib Attaiki, Lei Li, Maks Ovsjanikov:
Generalizable Local Feature Pre-training for Deformable Shape Analysis. CVPR 2023: 13650-13661 - [c60]Mingze Sun, Shiwei Mao, Puhua Jiang, Maks Ovsjanikov, Ruqi Huang:
Spatially and Spectrally Consistent Deep Functional Maps. ICCV 2023: 14451-14461 - [c59]Nissim Maruani, Roman Klokov, Maks Ovsjanikov, Pierre Alliez, Mathieu Desbrun:
VoroMesh: Learning Watertight Surface Meshes with Voronoi Diagrams. ICCV 2023: 14519-14528 - [c58]Ahmed Abdelreheem, Ivan Skorokhodov, Maks Ovsjanikov, Peter Wonka:
SATR: Zero-Shot Semantic Segmentation of 3D Shapes. ICCV 2023: 15120-15133 - [c57]Maysam Behmanesh, Maximilian Krahn, Maks Ovsjanikov:
TIDE: Time Derivative Diffusion for Deep Learning on Graphs. ICML 2023: 2015-2030 - [c56]Souhaib Attaiki, Maks Ovsjanikov:
Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction. NeurIPS 2023 - [c55]Ahmed Abdelreheem, Abdelrahman Eldesokey, Maks Ovsjanikov, Peter Wonka:
Zero-Shot 3D Shape Correspondence. SIGGRAPH Asia 2023: 59:1-59:11 - [i59]Souhaib Attaiki, Maks Ovsjanikov:
NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching. CoRR abs/2301.05839 (2023) - [i58]Robin Magnet, Maks Ovsjanikov:
Scalable and Efficient Functional Map Computations on Dense Meshes. CoRR abs/2303.05965 (2023) - [i57]Souhaib Attaiki, Lei Li, Maks Ovsjanikov:
Generalizable Local Feature Pre-training for Deformable Shape Analysis. CoRR abs/2303.15104 (2023) - [i56]Souhaib Attaiki, Maks Ovsjanikov:
Understanding and Improving Features Learned in Deep Functional Maps. CoRR abs/2303.16527 (2023) - [i55]Ahmed Abdelreheem, Ivan Skorokhodov, Maks Ovsjanikov, Peter Wonka:
SATR: Zero-Shot Semantic Segmentation of 3D Shapes. CoRR abs/2304.04909 (2023) - [i54]Ahmed Abdelreheem, Abdelrahman Eldesokey, Maks Ovsjanikov, Peter Wonka:
Zero-Shot 3D Shape Correspondence. CoRR abs/2306.03253 (2023) - [i53]Mingze Sun, Shiwei Mao, Puhua Jiang, Maks Ovsjanikov, Ruqi Huang:
Spatially and Spectrally Consistent Deep Functional Maps. CoRR abs/2308.08871 (2023) - [i52]Nissim Maruani, Roman Klokov, Maks Ovsjanikov, Pierre Alliez, Mathieu Desbrun:
VoroMesh: Learning Watertight Surface Meshes with Voronoi Diagrams. CoRR abs/2308.14616 (2023) - [i51]Vincent Mallet, Souhaib Attaiki, Maks Ovsjanikov:
AtomSurf : Surface Representation for Learning on Protein Structures. CoRR abs/2309.16519 (2023) - [i50]Sara Hahner, Souhaib Attaiki, Jochen Garcke, Maks Ovsjanikov:
Unsupervised Representation Learning for Diverse Deformable Shape Collections. CoRR abs/2310.18141 (2023) - [i49]Thomas Wimmer, Peter Wonka, Maks Ovsjanikov:
Back to 3D: Few-Shot 3D Keypoint Detection with Back-Projected 2D Features. CoRR abs/2311.18113 (2023) - 2022
- [j54]Nicolas Donati, Etienne Corman, Simone Melzi, Maks Ovsjanikov:
Complex Functional Maps: A Conformal Link Between Tangent Bundles. Comput. Graph. Forum 41(1): 317-334 (2022) - [j53]Luca Moschella, Simone Melzi, Luca Cosmo, Filippo Maggioli, Or Litany, Maks Ovsjanikov, Leonidas J. Guibas, Emanuele Rodolà:
Learning Spectral Unions of Partial Deformable 3D Shapes. Comput. Graph. Forum 41(2): 407-417 (2022) - [j52]Mikhail Panine, Maxime Kirgo, Maks Ovsjanikov:
Non-Isometric Shape Matching via Functional Maps on Landmark-Adapted Bases. Comput. Graph. Forum 41(6): 394-417 (2022) - [j51]Nicholas Sharp, Souhaib Attaiki, Keenan Crane, Maks Ovsjanikov:
DiffusionNet: Discretization Agnostic Learning on Surfaces. ACM Trans. Graph. 41(3): 27:1-27:16 (2022) - [c54]Lei Li, Souhaib Attaiki, Maks Ovsjanikov:
SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence. 3DV 2022: 144-154 - [c53]Robin Magnet, Jing Ren, Olga Sorkine-Hornung, Maks Ovsjanikov:
Smooth Non-Rigid Shape Matching via Effective Dirichlet Energy Optimization. 3DV 2022: 495-504 - [c52]Nicolas Donati, Etienne Corman, Maks Ovsjanikov:
Deep orientation-aware functional maps: Tackling symmetry issues in Shape Matching. CVPR 2022: 732-741 - [c51]Mariem Mezghanni, Théo Bodrito, Malika Boulkenafed, Maks Ovsjanikov:
Physical Simulation Layer for Accurate 3D Modeling. CVPR 2022: 13504-13513 - [c50]Ramana Sundararaman, Gautam Pai, Maks Ovsjanikov:
Implicit Field Supervision for Robust Non-rigid Shape Matching. ECCV (3) 2022: 344-362 - [c49]Emanuele Rodolà, Luca Cosmo, Maks Ovsjanikov, Arianna Rampini, Simone Melzi, Michael M. Bronstein, Riccardo Marin:
Inverse Computational Spectral Geometry. Eurographics (Tutorials) 2022 - [c48]Abhishek Sharma, Maks Ovsjanikov:
Matrix Decomposition on Graphs: A Simplified Functional View. ICASSP 2022: 3358-3362 - [c47]Lei Li, Nicolas Donati, Maks Ovsjanikov:
Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching. NeurIPS 2022 - [c46]Souhaib Attaiki, Maks Ovsjanikov:
NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matching. NeurIPS 2022 - [c45]Ramana Sundararaman, Riccardo Marin, Emanuele Rodolà, Maks Ovsjanikov:
Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching. NeurIPS 2022 - [i48]Ramana Sundararaman, Gautam Pai, Maks Ovsjanikov:
Implicit field supervision for robust non-rigid shape matching. CoRR abs/2203.07694 (2022) - [i47]Nicolas Donati, Etienne Corman, Maks Ovsjanikov:
Deep Orientation-Aware Functional Maps: Tackling Symmetry Issues in Shape Matching. CoRR abs/2204.13453 (2022) - [i46]Mikhail Panine, Maxime Kirgo, Maks Ovsjanikov:
Non-Isometric Shape Matching via Functional Maps on Landmark-Adapted Bases. CoRR abs/2205.04800 (2022) - [i45]Lei Li, Souhaib Attaiki, Maks Ovsjanikov:
SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence. CoRR abs/2209.07806 (2022) - [i44]Panos Achlioptas, Maks Ovsjanikov, Leonidas J. Guibas, Sergey Tulyakov:
Affection: Learning Affective Explanations for Real-World Visual Data. CoRR abs/2210.01946 (2022) - [i43]Robin Magnet, Jing Ren, Olga Sorkine-Hornung, Maks Ovsjanikov:
Smooth Non-Rigid Shape Matching via Effective Dirichlet Energy Optimization. CoRR abs/2210.02870 (2022) - [i42]Lei Li, Nicolas Donati, Maks Ovsjanikov:
Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching. CoRR abs/2210.06373 (2022) - [i41]Ramana Sundararaman, Riccardo Marin, Emanuele Rodolà, Maks Ovsjanikov:
Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching. CoRR abs/2211.14604 (2022) - [i40]Adrien Poulenard, Maks Ovsjanikov, Leonidas J. Guibas:
Equivalence Between SE(3) Equivariant Networks via Steerable Kernels and Group Convolution. CoRR abs/2211.15903 (2022) - [i39]Maximilian Krahn, Maysam Behmanesh, Maks Ovsjanikov:
TIDE: Time Derivative Diffusion for Deep Learning on Graphs. CoRR abs/2212.02483 (2022) - 2021
- [j50]Maxime Kirgo, Simone Melzi, Giuseppe Patanè, Emanuele Rodolà, Maks Ovsjanikov:
Wavelet-based Heat Kernel Derivatives: Towards Informative Localized Shape Analysis. Comput. Graph. Forum 40(1): 165-179 (2021) - [j49]Filippo Maggioli, Simone Melzi, Maksim Ovsjanikov, Michael M. Bronstein, Emanuele Rodolà:
Orthogonalized Fourier Polynomials for Signal Approximation and Transfer. Comput. Graph. Forum 40(2): 435-447 (2021) - [j48]Jing Ren, Simone Melzi, Peter Wonka, Maks Ovsjanikov:
Discrete Optimization for Shape Matching. Comput. Graph. Forum 40(5): 81-96 (2021) - [j47]Riccardo Marin, Arianna Rampini, Umberto Castellani, Emanuele Rodolà, Maks Ovsjanikov, Simone Melzi:
Spectral Shape Recovery and Analysis Via Data-driven Connections. Int. J. Comput. Vis. 129(10): 2745-2760 (2021) - [j46]Jing Ren, Biao Zhang, Bojian Wu, Jianqiang Huang, Lubin Fan, Maks Ovsjanikov, Peter Wonka:
Intuitive and efficient roof modeling for reconstruction and synthesis. ACM Trans. Graph. 40(6): 249:1-249:17 (2021) - [j45]Marie-Julie Rakotosaona, Noam Aigerman, Niloy J. Mitra, Maks Ovsjanikov, Paul Guerrero:
Differentiable surface triangulation. ACM Trans. Graph. 40(6): 267:1-267:13 (2021) - [c44]Souhaib Attaiki, Gautam Pai, Maks Ovsjanikov:
DPFM: Deep Partial Functional Maps. 3DV 2021: 175-185 - [c43]Marie-Julie Rakotosaona, Paul Guerrero, Noam Aigerman, Niloy J. Mitra, Maks Ovsjanikov:
Learning Delaunay Surface Elements for Mesh Reconstruction. CVPR 2021: 22-31 - [c42]Gautam Pai, Jing Ren, Simone Melzi, Peter Wonka, Maks Ovsjanikov:
Fast Sinkhorn Filters: Using Matrix Scaling for Non-Rigid Shape Correspondence With Functional Maps. CVPR 2021: 384-393 - [c41]Mariem Mezghanni, Malika Boulkenafed, André Lieutier, Maks Ovsjanikov:
Physically-Aware Generative Network for 3D Shape Modeling. CVPR 2021: 9330-9341 - [c40]Panos Achlioptas, Maks Ovsjanikov, Kilichbek Haydarov, Mohamed Elhoseiny, Leonidas J. Guibas:
ArtEmis: Affective Language for Visual Art. CVPR 2021: 11569-11579 - [c39]Robin Magnet, Maks Ovsjanikov:
DWKS : A Local Descriptor of Deformations Between Meshes and Point Clouds. ICCV 2021: 3773-3782 - [i38]Panos Achlioptas, Maks Ovsjanikov, Kilichbek Haydarov, Mohamed Elhoseiny, Leonidas J. Guibas:
ArtEmis: Affective Language for Visual Art. CoRR abs/2101.07396 (2021) - [i37]Abhishek Sharma, Maks Ovsjanikov:
Matrix Decomposition on Graphs: A Functional View. CoRR abs/2102.03233 (2021) - [i36]Luca Moschella, Simone Melzi, Luca Cosmo, Filippo Maggioli, Or Litany, Maks Ovsjanikov, Leonidas J. Guibas, Emanuele Rodolà:
Spectral Unions of Partial Deformable 3D Shapes. CoRR abs/2104.00514 (2021) - [i35]Lei Li, Hongbo Fu, Maks Ovsjanikov:
UPDesc: Unsupervised Point Descriptor Learning for Robust Registration. CoRR abs/2108.02740 (2021) - [i34]Jing Ren, Biao Zhang, Bojian Wu, Jianqiang Huang, Lubin Fan, Maks Ovsjanikov, Peter Wonka:
Intuitive and Efficient Roof Modeling for Reconstruction and Synthesis. CoRR abs/2109.07683 (2021) - [i33]Marie-Julie Rakotosaona, Noam Aigerman, Niloy J. Mitra, Maks Ovsjanikov, Paul Guerrero:
Differentiable Surface Triangulation. CoRR abs/2109.10695 (2021) - [i32]Abhishek Sharma, Maks Ovsjanikov:
Learning Canonical Embedding for Non-rigid Shape Matching. CoRR abs/2110.02994 (2021) - [i31]Souhaib Attaiki, Gautam Pai, Maks Ovsjanikov:
DPFM: Deep Partial Functional Maps. CoRR abs/2110.09994 (2021) - [i30]Abhishek Sharma, Maks Ovsjanikov:
Joint Symmetry Detection and Shape Matching for Non-Rigid Point Cloud. CoRR abs/2112.02713 (2021) - [i29]Riccardo Marin, Souhaib Attaiki, Simone Melzi, Emanuele Rodolà, Maks Ovsjanikov:
Why you should learn functional basis. CoRR abs/2112.07289 (2021) - [i28]Nicolas Donati, Etienne Corman, Simone Melzi, Maks Ovsjanikov:
Complex Functional Maps : a Conformal Link Between Tangent Bundles. CoRR abs/2112.09546 (2021) - 2020
- [j44]Marie-Julie Rakotosaona, Vittorio La Barbera, Paul Guerrero, Niloy J. Mitra, Maks Ovsjanikov:
PointCleanNet: Learning to Denoise and Remove Outliers from Dense Point Clouds. Comput. Graph. Forum 39(1): 185-203 (2020) - [j43]Thibault Lescoat, Hsueh-Ti Derek Liu, Jean-Marc Thiery, Alec Jacobson, Tamy Boubekeur, Maks Ovsjanikov:
Spectral Mesh Simplification. Comput. Graph. Forum 39(2): 315-324 (2020) - [j42]Ruqi Huang, Jing Ren, Peter Wonka, Maks Ovsjanikov:
Consistent ZoomOut: Efficient Spectral Map Synchronization. Comput. Graph. Forum 39(5): 265-278 (2020) - [j41]Jing Ren, Simone Melzi, Maks Ovsjanikov, Peter Wonka:
MapTree: recovering multiple solutions in the space of maps. ACM Trans. Graph. 39(6): 264:1-264:17 (2020) - [c38]Riccardo Marin, Arianna Rampini, Umberto Castellani, Emanuele Rodolà, Maks Ovsjanikov, Simone Melzi:
Instant recovery of shape from spectrum via latent space connections. 3DV 2020: 120-129 - [c37]Nicolas Donati, Abhishek Sharma, Maks Ovsjanikov:
Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence. CVPR 2020: 8589-8598 - [c36]Marie-Julie Rakotosaona, Maks Ovsjanikov:
Intrinsic Point Cloud Interpolation via Dual Latent Space Navigation. ECCV (2) 2020: 655-672 - [c35]Nicholas Sharp, Maks Ovsjanikov:
PointTriNet: Learned Triangulation of 3D Point Sets. ECCV (23) 2020: 762-778 - [c34]Riccardo Marin, Marie-Julie Rakotosaona, Simone Melzi, Maks Ovsjanikov:
Correspondence learning via linearly-invariant embedding. NeurIPS 2020 - [c33]Abhishek Sharma, Maks Ovsjanikov:
Weakly Supervised Deep Functional Maps for Shape Matching. NeurIPS 2020 - [i27]Riccardo Marin, Arianna Rampini, Umberto Castellani, Emanuele Rodolà, Maks Ovsjanikov, Simone Melzi:
Instant recovery of shape from spectrum via latent space connections. CoRR abs/2003.06523 (2020) - [i26]Nicolas Donati, Abhishek Sharma, Maks Ovsjanikov:
Deep Geometric Functional Maps: Robust Feature Learning for Shape Correspondence. CoRR abs/2003.14286 (2020) - [i25]Marie-Julie Rakotosaona, Maks Ovsjanikov:
Intrinsic Point Cloud Interpolation via Dual Latent Space Navigation. CoRR abs/2004.01661 (2020) - [i24]Nicholas Sharp, Maks Ovsjanikov:
PointTriNet: Learned Triangulation of 3D Point Sets. CoRR abs/2005.02138 (2020) - [i23]Jing Ren, Simone Melzi, Maks Ovsjanikov, Peter Wonka:
MapTree: Recovering Multiple Solutions in the Space of Maps. CoRR abs/2006.02532 (2020) - [i22]Maxime Kirgo, Simone Melzi, Giuseppe Patanè, Emanuele Rodolà, Maks Ovsjanikov:
Wavelet-based Heat Kernel Derivatives: Towards Informative Localized Shape Analysis. CoRR abs/2007.11632 (2020) - [i21]Abhishek Sharma, Maks Ovsjanikov:
Weakly Supervised Deep Functional Map for Shape Matching. CoRR abs/2009.13339 (2020) - [i20]Abhishek Sharma, Maks Ovsjanikov:
Geometric Matrix Completion: A Functional View. CoRR abs/2009.14343 (2020) - [i19]Jing Ren, Mikhail Panine, Peter Wonka, Maks Ovsjanikov:
Structured Regularization of Functional Map Computations. CoRR abs/2009.14624 (2020) - [i18]Riccardo Marin, Marie-Julie Rakotosaona, Simone Melzi, Maks Ovsjanikov:
Correspondence Learning via Linearly-invariant Embedding. CoRR abs/2010.13136 (2020) - [i17]Nicholas Sharp, Souhaib Attaiki, Keenan Crane, Maks Ovsjanikov:
Diffusion is All You Need for Learning on Surfaces. CoRR abs/2012.00888 (2020) - [i16]Marie-Julie Rakotosaona, Paul Guerrero, Noam Aigerman, Niloy J. Mitra, Maks Ovsjanikov:
Learning Delaunay Surface Elements for Mesh Reconstruction. CoRR abs/2012.01203 (2020)
2010 – 2019
- 2019
- [j40]Yanir Kleiman, Maks Ovsjanikov:
Robust Structure-Based Shape Correspondence. Comput. Graph. Forum 38(1): 7-20 (2019) - [j39]Jing Ren, Mikhail Panine, Peter Wonka, Maks Ovsjanikov:
Structured Regularization of Functional Map Computations. Comput. Graph. Forum 38(5): 39-53 (2019) - [j38]Ruqi Huang, Panos Achlioptas, Leonidas J. Guibas, Maks Ovsjanikov:
Limit Shapes - A Tool for Understanding Shape Differences and Variability in 3D Model Collections. Comput. Graph. Forum 38(5): 187-202 (2019) - [j37]Etienne Corman, Maks Ovsjanikov:
Functional Characterization of Deformation Fields. ACM Trans. Graph. 38(1): 8:1-8:19 (2019) - [j36]Hsueh-Ti Derek Liu, Alec Jacobson, Maks Ovsjanikov:
Spectral coarsening of geometric operators. ACM Trans. Graph. 38(4): 105:1-105:13 (2019) - [j35]Simone Melzi, Jing Ren, Emanuele Rodolà, Abhishek Sharma, Peter Wonka, Maks Ovsjanikov:
ZoomOut: spectral upsampling for efficient shape correspondence. ACM Trans. Graph. 38(6): 155:1-155:14 (2019) - [c32]Arianna Rampini, Irene Tallini, Maks Ovsjanikov, Alexander M. Bronstein, Emanuele Rodolà:
Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment. 3DV 2019: 37-46 - [c31]Adrien Poulenard, Marie-Julie Rakotosaona, Yann Ponty, Maks Ovsjanikov:
Effective Rotation-Invariant Point CNN with Spherical Harmonics Kernels. 3DV 2019: 47-56 - [c30]Simone Melzi, Riccardo Marin, Emanuele Rodolà, Umberto Castellani, Jing Ren, Adrien Poulenard, Peter Wonka, Maks Ovsjanikov:
Matching Humans with Different Connectivity. 3DOR@Eurographics 2019: 121-128 - [c29]Luca Cosmo, Mikhail Panine, Arianna Rampini, Maks Ovsjanikov, Michael M. Bronstein, Emanuele Rodolà:
Isospectralization, or How to Hear Shape, Style, and Correspondence. CVPR 2019: 7529-7538 - [c28]Jean-Michel Roufosse, Abhishek Sharma, Maks Ovsjanikov:
Unsupervised Deep Learning for Structured Shape Matching. ICCV 2019: 1617-1627 - [c27]Ruqi Huang, Marie-Julie Rakotosaona, Panos Achlioptas, Leonidas J. Guibas, Maks Ovsjanikov:
OperatorNet: Recovering 3D Shapes From Difference Operators. ICCV 2019: 8587-8596 - [c26]Thibault Lescoat, Pooran Memari, Jean-Marc Thiery, Maks Ovsjanikov, Tamy Boubekeur:
Connectivity-preserving Smooth Surface Filling with Sharp Features. PG (Short Papers) 2019: 7-13 - [i15]Marie-Julie Rakotosaona, Vittorio La Barbera, Paul Guerrero, Niloy J. Mitra, Maks Ovsjanikov:
POINTCLEANNET: Learning to Denoise and Remove Outliers from Dense Point Clouds. CoRR abs/1901.01060 (2019) - [i14]Simone Melzi, Jing Ren, Emanuele Rodolà, Peter Wonka, Maks Ovsjanikov:
ZoomOut: Spectral Upsampling for Efficient Shape Correspondence. CoRR abs/1904.07865 (2019) - [i13]Ruqi Huang, Marie-Julie Rakotosaona, Panos Achlioptas, Leonidas J. Guibas, Maks Ovsjanikov:
OperatorNet: Recovering 3D Shapes From Difference Operators. CoRR abs/1904.10754 (2019) - [i12]Hsueh-Ti Derek Liu, Alec Jacobson, Maks Ovsjanikov:
Spectral Coarsening of Geometric Operators. CoRR abs/1905.05161 (2019) - [i11]Arianna Rampini, Irene Tallini, Maks Ovsjanikov, Alexander M. Bronstein, Emanuele Rodolà:
Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment. CoRR abs/1906.06226 (2019) - [i10]Adrien Poulenard, Marie-Julie Rakotosaona, Yann Ponty, Maks Ovsjanikov:
Effective Rotation-invariant Point CNN with Spherical Harmonics kernels. CoRR abs/1906.11555 (2019) - 2018
- [j34]Guillaume Lavoué, Ioannis Pratikakis, Florent Dupont, Maks Ovsjanikov, Michela Spagnuolo:
Foreword to the Special Section on Eurographics Workshop on 3D Object Retrieval 2017. Comput. Graph. 71: 6- (2018) - [j33]Ruqi Huang, Frédéric Chazal, Maks Ovsjanikov:
On the Stability of Functional Maps and Shape Difference Operators. Comput. Graph. Forum 37(1): 145-158 (2018) - [j32]Paul Guerrero, Yanir Kleiman, Maks Ovsjanikov, Niloy J. Mitra:
PCPNet Learning Local Shape Properties from Raw Point Clouds. Comput. Graph. Forum 37(2): 75-85 (2018) - [j31]Dorian Nogneng, Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein, Maks Ovsjanikov:
Improved Functional Mappings via Product Preservation. Comput. Graph. Forum 37(2): 179-190 (2018) - [j30]Thibault Lescoat, Maks Ovsjanikov, Pooran Memari, Jean-Marc Thiery, Tamy Boubekeur:
A Survey on Data-driven Dictionary-based Methods for 3D Modeling. Comput. Graph. Forum 37(2): 577-601 (2018) - [j29]Adrien Poulenard, Primoz Skraba, Maks Ovsjanikov:
Topological Function Optimization for Continuous Shape Matching. Comput. Graph. Forum 37(5): 13-25 (2018) - [j28]Simone Melzi, Maks Ovsjanikov, Giorgio Roffo, Marco Cristani, Umberto Castellani:
Discrete Time Evolution Process Descriptor for Shape Analysis and Matching. ACM Trans. Graph. 37(1): 4 (2018) - [j27]Adrien Poulenard, Maks Ovsjanikov:
Multi-directional geodesic neural networks via equivariant convolution. ACM Trans. Graph. 37(6): 236 (2018) - [j26]Jing Ren, Adrien Poulenard, Peter Wonka, Maks Ovsjanikov:
Continuous and orientation-preserving correspondences via functional maps. ACM Trans. Graph. 37(6): 248 (2018) - [j25]Jing Ren, Jens Schneider, Maks Ovsjanikov, Peter Wonka:
Joint Graph Layouts for Visualizing Collections of Segmented Meshes. IEEE Trans. Vis. Comput. Graph. 24(9): 2546-2558 (2018) - [c25]Luca Castelli Aleardi, Semih Salihoglu, Gurprit Singh, Maks Ovsjanikov:
Spectral Measures of Distortion for Change Detection in Dynamic Graphs. COMPLEX NETWORKS (2) 2018: 54-66 - [i9]Ruqi Huang, Panos Achlioptas, Leonidas J. Guibas, Maks Ovsjanikov:
Latent Space Representation for Shape Analysis and Learning. CoRR abs/1806.03967 (2018) - [i8]Jing Ren, Adrien Poulenard, Peter Wonka, Maks Ovsjanikov:
Continuous and Orientation-preserving Correspondences via Functional Maps. CoRR abs/1806.04455 (2018) - [i7]Adrien Poulenard, Maks Ovsjanikov:
Multi-directional Geodesic Neural Networks via Equivariant Convolution. CoRR abs/1810.02303 (2018) - [i6]Luca Cosmo, Mikhail Panine, Arianna Rampini, Maks Ovsjanikov, Michael M. Bronstein, Emanuele Rodolà:
Isospectralization, or how to hear shape, style, and correspondence. CoRR abs/1811.11465 (2018) - [i5]Jean-Michel Roufosse, Maks Ovsjanikov:
Unsupervised Deep Learning for Structured Shape Matching. CoRR abs/1812.03794 (2018) - 2017
- [b1]Maks Ovsjanikov:
Functional View of Geometry Processing: Operator-based Techniques for Shape Analysis. University of Paris-Sud, Orsay, France, 2017 - [j24]Dorian Nogneng, Maks Ovsjanikov:
Informative Descriptor Preservation via Commutativity for Shape Matching. Comput. Graph. Forum 36(2): 259-267 (2017) - [j23]Ruqi Huang, Maks Ovsjanikov:
Adjoint Map Representation for Shape Analysis and Matching. Comput. Graph. Forum 36(5): 151-163 (2017) - [j22]Etienne Corman, Justin Solomon, Mirela Ben-Chen, Leonidas J. Guibas, Maks Ovsjanikov:
Functional Characterization of Intrinsic and Extrinsic Geometry. ACM Trans. Graph. 36(2): 14:1-14:17 (2017) - [j21]Omri Azencot, Etienne Corman, Mirela Ben-Chen, Maks Ovsjanikov:
Consistent functional cross field design for mesh quadrangulation. ACM Trans. Graph. 36(4): 92:1-92:13 (2017) - [c24]Matteo Denitto, Simone Melzi, Manuele Bicego, Umberto Castellani, Alessandro Farinelli, Mário A. T. Figueiredo, Yanir Kleiman, Maks Ovsjanikov:
Region-Based Correspondence Between 3D Shapes via Spatially Smooth Biclustering. ICCV 2017: 4270-4279 - [c23]Maks Ovsjanikov, Etienne Corman, Michael M. Bronstein, Emanuele Rodolà, Mirela Ben-Chen, Leonidas J. Guibas, Frédéric Chazal, Alexander M. Bronstein:
Computing and processing correspondences with functional maps. SIGGRAPH Courses 2017: 5:1-5:62 - [e1]Ioannis Pratikakis, Florent Dupont, Maks Ovsjanikov:
10th Eurographics Workshop on 3D Object Retrieval, 3DOR@Eurographics 2017, Lyon, France, April 23-24, 2017. Eurographics Association 2017, ISBN 978-3-03868-030-7 [contents] - [i4]Etienne Corman, Maks Ovsjanikov:
Functional Characterization of Deformation Fields. CoRR abs/1709.09701 (2017) - [i3]Paul Guerrero, Yanir Kleiman, Maks Ovsjanikov, Niloy J. Mitra:
PCPNET: Learning Local Shape Properties from Raw Point Clouds. CoRR abs/1710.04954 (2017) - [i2]Yanir Kleiman, Maks Ovsjanikov:
Robust Structure-based Shape Correspondence. CoRR abs/1710.05592 (2017) - [i1]Mirela Ben-Chen, Frédéric Chazal, Leonidas J. Guibas, Maks Ovsjanikov:
Functoriality in Geometric Data (Dagstuhl Seminar 17021). Dagstuhl Reports 7(1): 1-18 (2017) - 2016
- [j20]Vignesh Ganapathi-Subramanian, Boris Thibert, Maks Ovsjanikov, Leonidas J. Guibas:
Stable Region Correspondences Between Non-Isometric Shapes. Comput. Graph. Forum 35(5): 121-133 (2016) - [c22]Bo Li, Yijuan Lu, Fuqing Duan, Shuilong Dong, Yachun Fan, Lu Qian, Hamid Laga, Haisheng Li, Yuxiang Li, Peng Liu, Maks Ovsjanikov, Hedi Tabia, Yuxiang Ye, Huanpu Yin, Ziyu Xue:
3D Sketch-Based 3D Shape Retrieval. 3DOR@Eurographics 2016 - [c21]Thomas Bonis, Maks Ovsjanikov, Steve Oudot, Frédéric Chazal:
Persistence-Based Pooling for Shape Pose Recognition. CTIC 2016: 19-29 - [c20]Maks Ovsjanikov, Etienne Corman, Michael M. Bronstein, Emanuele Rodolà, Mirela Ben-Chen, Leonidas J. Guibas, Frédéric Chazal, Alexander M. Bronstein:
Computing and processing correspondences with functional maps. SIGGRAPH ASIA Courses 2016: 9:1-9:60 - [c19]Moos Hueting, Viorica Patraucean, Maks Ovsjanikov, Niloy J. Mitra:
Scene Structure Inference through Scene Map Estimation. VMV 2016 - 2015
- [j19]Mathieu Carrière, Steve Y. Oudot, Maks Ovsjanikov:
Stable Topological Signatures for Points on 3D Shapes. Comput. Graph. Forum 34(5): 1-12 (2015) - [j18]Etienne Corman, Maks Ovsjanikov, Antonin Chambolle:
Continuous Matching via Vector Field Flow. Comput. Graph. Forum 34(5): 129-139 (2015) - [j17]Omri Azencot, Maks Ovsjanikov, Frédéric Chazal, Mirela Ben-Chen:
Discrete Derivatives of Vector Fields on Surfaces - An Operator Approach. ACM Trans. Graph. 34(3): 29:1-29:13 (2015) - [j16]Moos Hueting, Maks Ovsjanikov, Niloy J. Mitra:
CrossLink: joint understanding of image and 3D model collections through shape and camera pose variations. ACM Trans. Graph. 34(6): 233:1-233:13 (2015) - [c18]Viorica Patraucean, Maks Ovsjanikov:
Affine invariant visual phrases for object instance recognition. MVA 2015: 14-17 - [c17]Luca Castelli Aleardi, Alexandre Nolin, Maks Ovsjanikov:
Efficient and Practical Tree Preconditioning for Solving Laplacian Systems. SEA 2015: 219-231 - 2014
- [j15]Omri Azencot, Steffen Weißmann, Maks Ovsjanikov, Max Wardetzky, Mirela Ben-Chen:
Functional Fluids on Surfaces. Comput. Graph. Forum 33(5): 237-246 (2014) - [c16]Andrea Giachetti, E. Mazzi, Francesco Piscitelli, Masaki Aono, A. Ben Hamza, Thomas Bonis, Peter Claes, Afzal Godil, Chunyuan Li, Maks Ovsjanikov, Viorica Patraucean, Chang Shu, J. Snyders, Paul Suetens, Atsushi Tatsuma, Dirk Vandermeulen, Stefanie Wuhrer, Pengcheng Xi:
Automatic Location of Landmarks used in Manual Anthropometry. 3DOR@Eurographics 2014: 93-100 - [c15]Chunyuan Li, Maks Ovsjanikov, Frédéric Chazal:
Persistence-Based Structural Recognition. CVPR 2014: 2003-2010 - [c14]Fan Wang, Qixing Huang, Maks Ovsjanikov, Leonidas J. Guibas:
Unsupervised Multi-class Joint Image Segmentation. CVPR 2014: 3142-3149 - [c13]Etienne Corman, Maks Ovsjanikov, Antonin Chambolle:
Supervised Descriptor Learning for Non-Rigid Shape Matching. ECCV Workshops (4) 2014: 283-298 - 2013
- [j14]Maks Ovsjanikov, Quentin Mérigot, Viorica Patraucean, Leonidas J. Guibas:
Shape Matching via Quotient Spaces. Comput. Graph. Forum 32(5): 1-11 (2013) - [j13]Omri Azencot, Mirela Ben-Chen, Frédéric Chazal, Maks Ovsjanikov:
An Operator Approach to Tangent Vector Field Processing. Comput. Graph. Forum 32(5): 73-82 (2013) - [j12]Maks Ovsjanikov, Mirela Ben-Chen, Frédéric Chazal, Leonidas J. Guibas:
Analysis and Visualization of Maps Between Shapes. Comput. Graph. Forum 32(6): 135-145 (2013) - [j11]Raif M. Rustamov, Maks Ovsjanikov, Omri Azencot, Mirela Ben-Chen, Frédéric Chazal, Leonidas J. Guibas:
Map-based exploration of intrinsic shape differences and variability. ACM Trans. Graph. 32(4): 72:1-72:12 (2013) - [c12]Viorica Patraucean, Rafael Grompone von Gioi, Maks Ovsjanikov:
Detection of Mirror-Symmetric Image Patches. CVPR Workshops 2013: 211-216 - [c11]Niloy J. Mitra, Maksim Ovsjanikov, Mark Pauly, Michael Wand, Duygu Ceylan:
Symmetry in Shapes - Theory and Practice. Eurographics (Tutorials) 2013 - 2012
- [j10]Maks Ovsjanikov, Mirela Ben-Chen, Justin Solomon, Adrian Butscher, Leonidas J. Guibas:
Functional maps: a flexible representation of maps between shapes. ACM Trans. Graph. 31(4): 30:1-30:11 (2012) - [p1]Alexander M. Bronstein, Michael M. Bronstein, Maks Ovsjanikov:
Feature-Based Methods in 3D Shape Analysis. 3D Imaging, Analysis and Applications 2012: 185-219 - 2011
- [j9]Maks Ovsjanikov, Qi-Xing Huang, Leonidas J. Guibas:
A Condition Number for Non-Rigid Shape Matching. Comput. Graph. Forum 30(5): 1503-1512 (2011) - [j8]Alexander M. Bronstein, Michael M. Bronstein, Leonidas J. Guibas, Maks Ovsjanikov:
Shape google: Geometric words and expressions for invariant shape retrieval. ACM Trans. Graph. 30(1): 1:1-1:20 (2011) - [j7]Maks Ovsjanikov, Wilmot Li, Leonidas J. Guibas, Niloy J. Mitra:
Exploration of continuous variability in collections of 3D shapes. ACM Trans. Graph. 30(4): 33 (2011) - [j6]Quentin Mérigot, Maks Ovsjanikov, Leonidas J. Guibas:
Voronoi-Based Curvature and Feature Estimation from Point Clouds. IEEE Trans. Vis. Comput. Graph. 17(6): 743-756 (2011) - 2010
- [j5]Bart Adams, Martin Wicke, Maks Ovsjanikov, Michael Wand, Hans-Peter Seidel, Leonidas J. Guibas:
Meshless Shape and Motion Design for Multiple Deformable Objects. Comput. Graph. Forum 29(1): 43-59 (2010) - [j4]Maks Ovsjanikov, Quentin Mérigot, Facundo Mémoli, Leonidas J. Guibas:
One Point Isometric Matching with the Heat Kernel. Comput. Graph. Forum 29(5): 1555-1564 (2010) - [c10]Alexander M. Bronstein, Michael M. Bronstein, Umberto Castellani, Bianca Falcidieno, Andrea Fusiello, Afzal Godil, Leonidas J. Guibas, Iasonas Kokkinos, Zhouhui Lian, Maks Ovsjanikov, Giuseppe Patanè, Michela Spagnuolo, Roberto Toldo:
SHREC'10 Track: Robust Shape Retrieval. 3DOR@Eurographics 2010: 71-78 - [c9]Alexander M. Bronstein, Michael M. Bronstein, Benjamin Bustos, Umberto Castellani, Marco Cristani, Bianca Falcidieno, Leonidas J. Guibas, Iasonas Kokkinos, Vittorio Murino, Maks Ovsjanikov, Giuseppe Patanè, Ivan Sipiran, Michela Spagnuolo, Jian Sun:
SHREC'10 Track: Feature Detection and Description. 3DOR@Eurographics 2010: 79-86 - [c8]Alexander M. Bronstein, Michael M. Bronstein, Umberto Castellani, Anastasia Dubrovina, Leonidas J. Guibas, Radu Horaud, Ron Kimmel, David Knossow, Etienne von Lavante, Diana Mateus, Maks Ovsjanikov, Avinash Sharma:
SHREC'10 Track: Correspondence Finding. 3DOR@Eurographics 2010: 87-91 - [c7]Primoz Skraba, Maks Ovsjanikov, Frédéric Chazal, Leonidas J. Guibas:
Persistence-based segmentation of deformable shapes. CVPR Workshops 2010: 45-52 - [c6]Kyle Heath, Natasha Gelfand, Maks Ovsjanikov, Mridul Aanjaneya, Leonidas J. Guibas:
Image webs: Computing and exploiting connectivity in image collections. CVPR 2010: 3432-3439 - [c5]Maks Ovsjanikov, Ye Chen:
Topic Modeling for Personalized Recommendation of Volatile Items. ECML/PKDD (2) 2010: 483-498
2000 – 2009
- 2009
- [j3]Jian Sun, Maks Ovsjanikov, Leonidas J. Guibas:
A Concise and Provably Informative Multi-Scale Signature Based on Heat Diffusion. Comput. Graph. Forum 28(5): 1383-1392 (2009) - [j2]Michael Wand, Bart Adams, Maks Ovsjanikov, Alexander Berner, Martin Bokeloh, Philipp Jenke, Leonidas J. Guibas, Hans-Peter Seidel, Andreas Schilling:
Efficient reconstruction of nonrigid shape and motion from real-time 3D scanner data. ACM Trans. Graph. 28(2): 15:1-15:15 (2009) - [c4]Maks Ovsjanikov, Alexander M. Bronstein, Michael M. Bronstein, Leonidas J. Guibas:
Shape Google: a computer vision approach to isometry invariant shape retrieval. ICCV Workshops 2009: 320-327 - [c3]Quentin Mérigot, Maks Ovsjanikov, Leonidas J. Guibas:
Robust Voronoi-based curvature and feature estimation. Symposium on Solid and Physical Modeling 2009: 1-12 - 2008
- [j1]Maks Ovsjanikov, Jian Sun, Leonidas J. Guibas:
Global Intrinsic Symmetries of Shapes. Comput. Graph. Forum 27(5): 1341-1348 (2008) - [c2]Bart Adams, Maks Ovsjanikov, Michael Wand, Hans-Peter Seidel, Leonidas J. Guibas:
Meshless Modeling of Deformable Shapes and their Motion. Symposium on Computer Animation 2008: 77-86 - 2007
- [c1]Niloy J. Mitra, Simon Flöry, Maks Ovsjanikov, Natasha Gelfand, Leonidas J. Guibas, Helmut Pottmann:
Dynamic geometry registration. Symposium on Geometry Processing 2007: 173-182
Coauthor Index
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