Skip to content
/ RLFN Public

Winner of runtime track in NTIRE 2022 challenge on Efficient Super-Resolution

License

Notifications You must be signed in to change notification settings

bytedance/RLFN

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Residual Local Feature Network

Our team (ByteESR) won the first place in Runtime Track (Main Track) and the second place in Overall Performance Track (Sub-Track 2) of NTIRE 2022 Efficient Super-Resolution Challenge.

model Runtime[ms] Params[M] Flops[G] Acts[M] GPU Mem[M]
RLFN_ntire 27.11 0.317 19.70 80.05 377.91

Open-Source

For commercial reasons, we don't release training code temporarily, please refer to EDSR framework and our paper for details.

Testing

We modified the official test code. To reproduce our result in the ESR challenge, please install PyTorch >= 1.5.0.

run python test_demo.py to generate image results.
All test results will be saved in the folder data/DIV2K_test_LR_results

About

Winner of runtime track in NTIRE 2022 challenge on Efficient Super-Resolution

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages