[{"oa_version":"Preprint","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.1906.06226","open_access":"1"}],"date_created":"2024-10-08T13:07:51Z","citation":{"mla":"Rampini, Arianna, et al. “Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment.” <i>2019 International Conference on 3D Vision (3DV)</i>, 8886146, IEEE, 2019, doi:<a href=\"https://doi.org/10.1109/3dv.2019.00014\">10.1109/3dv.2019.00014</a>.","apa":"Rampini, A., Tallini, I., Ovsjanikov, M., Bronstein, A. M., &#38; Rodola, E. (2019). Correspondence-free region localization for partial shape similarity via Hamiltonian spectrum alignment. In <i>2019 International Conference on 3D Vision (3DV)</i>. Quebec City, QC, Canada: IEEE. <a href=\"https://doi.org/10.1109/3dv.2019.00014\">https://doi.org/10.1109/3dv.2019.00014</a>","chicago":"Rampini, Arianna, Irene Tallini, Maks Ovsjanikov, Alex M. Bronstein, and Emanuele Rodola. “Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment.” In <i>2019 International Conference on 3D Vision (3DV)</i>. IEEE, 2019. <a href=\"https://doi.org/10.1109/3dv.2019.00014\">https://doi.org/10.1109/3dv.2019.00014</a>.","ama":"Rampini A, Tallini I, Ovsjanikov M, Bronstein AM, Rodola E. Correspondence-free region localization for partial shape similarity via Hamiltonian spectrum alignment. In: <i>2019 International Conference on 3D Vision (3DV)</i>. IEEE; 2019. doi:<a href=\"https://doi.org/10.1109/3dv.2019.00014\">10.1109/3dv.2019.00014</a>","ieee":"A. Rampini, I. Tallini, M. Ovsjanikov, A. M. Bronstein, and E. Rodola, “Correspondence-free region localization for partial shape similarity via Hamiltonian spectrum alignment,” in <i>2019 International Conference on 3D Vision (3DV)</i>, Quebec City, QC, Canada, 2019.","short":"A. Rampini, I. Tallini, M. Ovsjanikov, A.M. Bronstein, E. Rodola, in:, 2019 International Conference on 3D Vision (3DV), IEEE, 2019.","ista":"Rampini A, Tallini I, Ovsjanikov M, Bronstein AM, Rodola E. 2019. Correspondence-free region localization for partial shape similarity via Hamiltonian spectrum alignment. 2019 International Conference on 3D Vision (3DV). 7th International Conference on 3D Vision, 8886146."},"date_published":"2019-10-31T00:00:00Z","month":"10","quality_controlled":"1","date_updated":"2024-12-05T15:49:06Z","oa":1,"day":"31","doi":"10.1109/3dv.2019.00014","publication_identifier":{"isbn":["9781728131320"],"eissn":["2475-7888"]},"status":"public","language":[{"iso":"eng"}],"external_id":{"arxiv":["1906.06226"]},"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","publication":"2019 International Conference on 3D Vision (3DV)","year":"2019","extern":"1","author":[{"full_name":"Rampini, Arianna","last_name":"Rampini","first_name":"Arianna"},{"full_name":"Tallini, Irene","last_name":"Tallini","first_name":"Irene"},{"last_name":"Ovsjanikov","first_name":"Maks","full_name":"Ovsjanikov, Maks"},{"id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","orcid":"0000-0001-9699-8730","first_name":"Alexander","last_name":"Bronstein"},{"full_name":"Rodola, Emanuele","last_name":"Rodola","first_name":"Emanuele"}],"scopus_import":"1","_id":"18257","publication_status":"published","conference":{"end_date":"2019-09-19","location":"Quebec City, QC, Canada","start_date":"2019-09-16","name":"7th International Conference on 3D Vision"},"article_processing_charge":"No","arxiv":1,"article_number":"8886146","type":"conference","fulldoi":"https://doi.org/10.1109/3dv.2019.00014","abstract":[{"lang":"eng","text":"We consider the problem of localizing relevant subsets of non-rigid geometric shapes given only a partial 3D query as the input. Such problems arise in several challenging tasks in 3D vision and graphics, including partial shape similarity, retrieval, and non-rigid correspondence. We phrase the problem as one of alignment between short sequences of eigenvalues of basic differential operators, which are constructed upon a scalar function defined on the 3D surfaces. Our method therefore seeks for a scalar function that entails this alignment. Differently from existing approaches, we do not require solving for a correspondence between the query and the target, therefore greatly simplifying the optimization process; our core technique is also descriptor-free, as it is driven by the geometry of the two objects as encoded in their operator spectra. We further show that our spectral alignment algorithm provides a remarkably simple alternative to the recent shape-from-spectrum reconstruction approaches. For both applications, we demonstrate improvement over the state-of-the-art either in terms of accuracy or computational cost."}],"title":"Correspondence-free region localization for partial shape similarity via Hamiltonian spectrum alignment","publisher":"IEEE"}]