Exploiting the image prior in CLIP for super-resolution

Super-resolution (SR) is a fundamental task in computer vision aimed at enhancing the resolution and quality of low-resolution images. However, a persistent challenge arises from the inherent ambiguity where a single low-resolution image may correspond to mul- tiple high-resolution images. Additiona...

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Main Author: Chen, Xingyu
Other Authors: Chen Change Loy
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
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Online Access:https://hdl.handle.net/10356/175133
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1751332024-04-26T15:40:52Z Exploiting the image prior in CLIP for super-resolution Chen, Xingyu Chen Change Loy School of Computer Science and Engineering ccloy@ntu.edu.sg Computer and Information Science Super resolution Computer vision CLIP Deep learning Super-resolution (SR) is a fundamental task in computer vision aimed at enhancing the resolution and quality of low-resolution images. However, a persistent challenge arises from the inherent ambiguity where a single low-resolution image may correspond to mul- tiple high-resolution images. Additional priors are essential to address such problem, especially when the degradation is complex. Recent emergence of large vision-language model such as CLIP provides potential to enhance SR generation by providing extra con- textual information from the image. Hence, in this project, we investigate the efficacy of integrating CLIP priors into image super-resolution. Through a series of experiments, we explore both blind and non-blind SR problems, evaluating the impact of CLIP priors on model performance. Additionally, we analyze the limitations and challenges associated with CLIP integration, particularly in handling low-resolution and incomplete images. Our findings demonstrate that while CLIP priors hold promise in enhancing SR results, careful fine-tuning is required to optimize their utilization for image generation tasks. Bachelor's degree 2024-04-22T02:49:53Z 2024-04-22T02:49:53Z 2024 Final Year Project (FYP) Chen, X. (2024). Exploiting the image prior in CLIP for super-resolution. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175133 https://hdl.handle.net/10356/175133 en SCSE23-0477 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Computer and Information Science
Super resolution
Computer vision
CLIP
Deep learning
spellingShingle Computer and Information Science
Super resolution
Computer vision
CLIP
Deep learning
Chen, Xingyu
Exploiting the image prior in CLIP for super-resolution
description Super-resolution (SR) is a fundamental task in computer vision aimed at enhancing the resolution and quality of low-resolution images. However, a persistent challenge arises from the inherent ambiguity where a single low-resolution image may correspond to mul- tiple high-resolution images. Additional priors are essential to address such problem, especially when the degradation is complex. Recent emergence of large vision-language model such as CLIP provides potential to enhance SR generation by providing extra con- textual information from the image. Hence, in this project, we investigate the efficacy of integrating CLIP priors into image super-resolution. Through a series of experiments, we explore both blind and non-blind SR problems, evaluating the impact of CLIP priors on model performance. Additionally, we analyze the limitations and challenges associated with CLIP integration, particularly in handling low-resolution and incomplete images. Our findings demonstrate that while CLIP priors hold promise in enhancing SR results, careful fine-tuning is required to optimize their utilization for image generation tasks.
author2 Chen Change Loy
author_facet Chen Change Loy
Chen, Xingyu
format Final Year Project
author Chen, Xingyu
author_sort Chen, Xingyu
title Exploiting the image prior in CLIP for super-resolution
title_short Exploiting the image prior in CLIP for super-resolution
title_full Exploiting the image prior in CLIP for super-resolution
title_fullStr Exploiting the image prior in CLIP for super-resolution
title_full_unstemmed Exploiting the image prior in CLIP for super-resolution
title_sort exploiting the image prior in clip for super-resolution
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/175133
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