Cross-Resolution-Flow-Propagation-for-Foveated-Video-Super-Resolution

Official implementation of Cross-Resolution Flow Propagation for Foveated Video Super-Resolution (CRFP) accepted by WACV 2023.

Demo

Demonstration how CRFP deal with various value of $\sigma^T$ representing the noise induced by the movement of eye tracker during pupil detection. Note that regions beyond the foveated region are resolved under $8\times$ super-resolution.

$\sigma^T=10$

$\sigma^T=50$

$\sigma^T=100$

Training and evaluation

To train the model, you need to install DCN first from https://github.com/jinfagang/DCNv2_latest

Run the following to start training

bash train.sh

To evaluate, run

bash eval.sh

To test, run

bash test.sh

References

Most of the code is referenced from

1. TTSR: https://github.com/researchmm/TTSR
2. BasicVSR: https://github.com/open-mmlab/mmediting