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Reference-based Super-Resolution

Reference-based Super-Resolution aims to recover high-resolution images by utilizing external reference images containing similar content to generate rich textures.

Papers

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Showing 1–10 of 26 papers

TitleStatusHype
HiTSR: A Hierarchical Transformer for Reference-based Super-ResolutionCode0
Sewer Image Super-Resolution with Depth Priors and Its Lightweight Network—0
MaRINeR: Enhancing Novel Views by Matching Rendered Images with Nearby ReferencesCode1
Self-Supervised Learning for Real-World Super-Resolution from Dual and Multiple Zoomed ObservationsCode2
Detail-Enhancing Framework for Reference-Based Image Super-Resolution—0
Building Bridges across Spatial and Temporal Resolutions: Reference-Based Super-Resolution via Change Priors and Conditional Diffusion ModelCode2
HSTR-Net: Reference Based Video Super-resolution with Dual Cameras—0
A Feature Reuse Framework with Texture-adaptive Aggregation for Reference-based Super-ResolutionCode1
Reference-based OCT Angiogram Super-resolution with Learnable Texture Generation—0
LMR: A Large-Scale Multi-Reference Dataset for Reference-based Super-ResolutionCode1
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