Non-Rigid 3D Shape Correspondences: From Foundations to Open Challenges and Opportunities
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arXiv
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| Autores principales: | , , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866918423942922240 |
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| author | Zhuravlev, Aleksei Bastian, Lennart Cao, Dongliang Amrani, Nafie El Roetzer, Paul Ehm, Viktoria Marin, Riccardo Nishizawa, Hiroki Morishima, Shigeo Theobalt, Christian Navab, Nassir Cremers, Daniel Bernard, Florian Lähner, Zorah Golyanik, Vladislav |
| author_facet | Zhuravlev, Aleksei Bastian, Lennart Cao, Dongliang Amrani, Nafie El Roetzer, Paul Ehm, Viktoria Marin, Riccardo Nishizawa, Hiroki Morishima, Shigeo Theobalt, Christian Navab, Nassir Cremers, Daniel Bernard, Florian Lähner, Zorah Golyanik, Vladislav |
| contents | Estimating correspondences between deformed shape instances is a long-standing problem in computer graphics; numerous applications, from texture transfer to statistical modelling, rely on recovering an accurate correspondence map. Many methods have thus been proposed to tackle this challenging problem from varying perspectives, depending on the downstream application. This state-of-the-art report is geared towards researchers, practitioners, and students seeking to understand recent trends and advances in the field. We categorise developments into three paradigms: spectral methods based on functional maps, combinatorial formulations that impose discrete constraints, and deformation-based methods that directly recover a global alignment. Each school of thought offers different advantages and disadvantages, which we discuss throughout the report. Meanwhile, we highlight the latest developments in each area and suggest new potential research directions. Finally, we provide an overview of emerging challenges and opportunities in this growing field, including the recent use of vision foundation models for zero-shot correspondence and the particularly challenging task of matching partial shapes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_01274 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Non-Rigid 3D Shape Correspondences: From Foundations to Open Challenges and Opportunities Zhuravlev, Aleksei Bastian, Lennart Cao, Dongliang Amrani, Nafie El Roetzer, Paul Ehm, Viktoria Marin, Riccardo Nishizawa, Hiroki Morishima, Shigeo Theobalt, Christian Navab, Nassir Cremers, Daniel Bernard, Florian Lähner, Zorah Golyanik, Vladislav Graphics Computer Vision and Pattern Recognition Estimating correspondences between deformed shape instances is a long-standing problem in computer graphics; numerous applications, from texture transfer to statistical modelling, rely on recovering an accurate correspondence map. Many methods have thus been proposed to tackle this challenging problem from varying perspectives, depending on the downstream application. This state-of-the-art report is geared towards researchers, practitioners, and students seeking to understand recent trends and advances in the field. We categorise developments into three paradigms: spectral methods based on functional maps, combinatorial formulations that impose discrete constraints, and deformation-based methods that directly recover a global alignment. Each school of thought offers different advantages and disadvantages, which we discuss throughout the report. Meanwhile, we highlight the latest developments in each area and suggest new potential research directions. Finally, we provide an overview of emerging challenges and opportunities in this growing field, including the recent use of vision foundation models for zero-shot correspondence and the particularly challenging task of matching partial shapes. |
| title | Non-Rigid 3D Shape Correspondences: From Foundations to Open Challenges and Opportunities |
| topic | Graphics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2604.01274 |