A Hybrid CNN-Transformer Architecture with Frequency Domain Contrastive Learning for Image Deraining
arXiv:2308.03340v13 citationsh-index: 4
Originality Synthesis-oriented
AI Analysis
This work addresses image quality enhancement for computer vision applications, but appears incremental as it combines existing methods.
The paper tackled the problem of restoring images degraded by rain streaks, achieving improved performance through a hybrid CNN-Transformer architecture with frequency domain contrastive learning.
Image deraining is a challenging task that involves restoring degraded images affected by rain streaks.