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rlfn's Introduction

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

rlfn's People

Contributors

fyan111 avatar

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