Multi-Attention Based Ultra Lightweight Image Super-Resolution

Understand

Lightweight image super-resolution (SR) networks have the utmost significance for real-world applications.

• There are several deep learning based SR methods with remarkable performance, but their memory and computational cost are hindrances in practical usage.
• To tackle this problem, we propose a Multi-Attentive Feature Fusion Super-Resolution Network (MAFFSRN).
• MAFFSRN consists of proposed feature fusion groups (FFGs) that serve as a feature extraction block.