Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Lee, Jaewon | - |
dc.contributor.author | Choi, Kwang Pyo | - |
dc.contributor.author | Jin, Kyong Hwan | - |
dc.date.accessioned | 2023-12-26T18:12:24Z | - |
dc.date.available | 2023-12-26T18:12:24Z | - |
dc.date.created | 2022-12-30 | - |
dc.date.issued | 2022-10-26 | - |
dc.identifier.isbn | 9783031197963 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/46790 | - |
dc.description.abstract | Image warping aims to reshape images defined on rectangular grids into arbitrary shapes. Recently, implicit neural functions have shown remarkable performances in representing images in a continuous manner. However, a standalone multi-layer perceptron suffers from learning high-frequency Fourier coefficients. In this paper, we propose a local texture estimator for image warping (LTEW) followed by an implicit neural representation to deform images into continuous shapes. Local textures estimated from a deep super-resolution (SR) backbone are multiplied by locally-varying Jacobian matrices of a coordinate transformation to predict Fourier responses of a warped image. Our LTEW-based neural function outperforms existing warping methods for asymmetric-scale SR and homography transform. Furthermore, our algorithm well generalizes arbitrary coordinate transformations, such as homography transform with a large magnification factor and equirectangular projection (ERP) perspective transform, which are not provided in training. Our source code is available at https://github.com/jaewon-lee-b/ltew. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. | - |
dc.language | English | - |
dc.publisher | European Conference on Computer Vision | - |
dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.title | Learning Local Implicit Fourier Representation for Image Warping | - |
dc.type | Conference Paper | - |
dc.identifier.doi | 10.1007/978-3-031-19797-0_11 | - |
dc.identifier.wosid | 000904379300011 | - |
dc.identifier.scopusid | 2-s2.0-85142727227 | - |
dc.identifier.bibliographicCitation | European Conference on Computer Vision (poster), pp.182 - 200 | - |
dc.identifier.url | https://eccv2022.ecva.net/files/2021/12/ECCV_2022_MainConference_ProgramGuide_Final_full.pdf | - |
dc.citation.conferenceDate | 2022-10-23 | - |
dc.citation.conferencePlace | IS | - |
dc.citation.conferencePlace | Tel Aviv | - |
dc.citation.endPage | 200 | - |
dc.citation.startPage | 182 | - |
dc.citation.title | European Conference on Computer Vision (poster) | - |
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