1Korea Advanced Institute of Science and Technology, South Korea
2Chung-Ang University, South Korea
This repository is the official PyTorch implementation of "FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurring". FMA-Net achieves state-of-the-art performance in joint video super-resolution and deblurring (VSRDB).
Please visit our project page for more visual results.
🎬 Network Architecture
Codes and pretrained models will be updated soon.
News
Feb 27, 2024: FMA-Net accepted at CVPR 2024 🎉
Jan 14, 2024: This repository is created
Reference
@inproceedings{youk2024fmanet,
author = {Geunhyuk Youk and Jihyong Oh and Munchurl Kim},
title = {FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurring},
booktitle = {CVPR},
year = {2024},
}