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eess.IV2024
Unveiling Hidden Details: A RAW Data-Enhanced Paradigm for Real-World Super-Resolution
Long Peng, Wenbo Li, Jiaming Guo +7
Real-world image super-resolution (Real SR) aims to generate high-fidelity, detail-rich high-resolution (HR) images from low-resolution (LR) counterparts. Existing Real SR methods…
eess.IV2024
Efficient Real-world Image Super-Resolution Via Adaptive Directional Gradient Convolution
Long Peng, Yang Cao, Renjing Pei +5
Real-SR endeavors to produce high-resolution images with rich details while mitigating the impact of multiple degradation factors. Although existing methods have achieved impressiv…
eess.IV2024
Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning
Haoyu Chen, Wenbo Li, Jinjin Gu +6
For image super-resolution (SR), bridging the gap between the performance on synthetic datasets and real-world degradation scenarios remains a challenge. This work introduces a nov…