5 citations · 9 across the 8 of their papers we have counts for
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eess.IV2021
Frequency-Aware Physics-Inspired Degradation Model for Real-World Image Super-Resolution
Zhenxing Dong, Hong Cao, Wang Shen +4
Current learning-based single image super-resolution (SISR) algorithms underperform on real data due to the deviation in the assumed degrada-tion process from that in the real-worl…
cs.LG2021★ 1 cited
Co-Seg: An Image Segmentation Framework Against Label Corruption
Ziyi Huang, Haofeng Zhang, Andrew Laine +3
Supervised deep learning performance is heavily tied to the availability of high-quality labels for training. Neural networks can gradually overfit corrupted labels if directly tra…