20 citations · 42 across the 11 of their papers we have counts for
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cs.CV2023
Beyond Image Borders: Learning Feature Extrapolation for Unbounded Image Composition
Xiaoyu Liu, Ming Liu, Junyi Li +4
For improving image composition and aesthetic quality, most existing methods modulate the captured images by striking out redundant content near the image borders. However, such im…
cs.CV2023
MetaF2N: Blind Image Super-Resolution by Learning Efficient Model Adaptation from Faces
Zhicun Yin, Ming Liu, Xiaoming Li +3
Due to their highly structured characteristics, faces are easier to recover than natural scenes for blind image super-resolution. Therefore, we can extract the degradation represen…
cs.CV2023
Human Guided Ground-truth Generation for Realistic Image Super-resolution
Du Chen, Jie Liang, Xindong Zhang +3
How to generate the ground-truth (GT) image is a critical issue for training realistic image super-resolution (Real-ISR) models. Existing methods mostly take a set of high-resoluti…