Multi-Scale Implicit Transformer with Re-parameterize for Arbitrary-Scale Super-Resolution Article Swipe
Jinchen Zhu
,
Dongke Zhang
,
Ling Zheng
,
Shizhuang Weng
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2403.06536
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2403.06536
Recently, the methods based on implicit neural representations have shown excellent capabilities for arbitrary-scale super-resolution (ASSR). Although these methods represent the features of an image by generating latent codes, these latent codes are difficult to adapt for different magnification factors of super-resolution, which seriously affects their performance. Addressing this, we design Multi-Scale Implicit Transformer (MSIT), consisting of an Multi-scale Neural Operator (MSNO) and Multi-Scale Self-Attention (MSSA). Among them, MSNO obtains multi-scale latent codes through feature enhancement, multi-scale characteristics extraction, and multi-scale characteristics merging. MSSA further enhances the multi-scale characteristics of latent codes, resulting in better performance. Furthermore, to improve the performance of network, we propose the Re-Interaction Module (RIM) combined with the cumulative training strategy to improve the diversity of learned information for the network. We have systematically introduced multi-scale characteristics for the first time in ASSR, extensive experiments are performed to validate the effectiveness of MSIT, and our method achieves state-of-the-art performance in arbitrary super-resolution tasks.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2403.06536
- https://arxiv.org/pdf/2403.06536
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392736053
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- OpenAlex ID
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https://openalex.org/W4392736053Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2403.06536Digital Object Identifier
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Multi-Scale Implicit Transformer with Re-parameterize for Arbitrary-Scale Super-ResolutionWork title
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-03-11Full publication date if available
- Authors
-
Jinchen Zhu, Dongke Zhang, Ling Zheng, Shizhuang WengList of authors in order
- Landing page
-
https://arxiv.org/abs/2403.06536Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2403.06536Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2403.06536Direct OA link when available
- Concepts
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Transformer, Scale (ratio), Computer science, Environmental science, Electrical engineering, Engineering, Geography, Cartography, VoltageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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