121644048 / SplitSR

SplitSR: An End-to-End Approach to Super-Resolution on Mobile Devices (Unofficial Implementation)

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SplitSR

Unofficial implementation of SplitSR: An End-to-End Approach to Super-Resolution on Mobile Devices

a) SplitSRBlock, b) SplitSR

Keys from the Paper

  • Split convolution splits input by alpha ratio along depth channel.
  • The conv-processed part is concatenated at the end.
  • By the second key point, every channel would be processed after 1/α blocks.
  • The theoretical computation reduction that can be obtained by using SplitSR is 𝛼^2, where 𝛼 ∈ (0, 1]
  • The architecture is very much similar to RCAN's, by replacing channelwise attention blocks with split convolutions.
  • Many proposed details are ambiguous. We've to guess.

Config

  • 𝛼 = 0.250
  • Groups = 6, Blocks = 6
  • Hybrid Index = 3
  • Loss - L1
  • Base LR - 1e-4
  • LR Decay - 2.0 every 2 × 10^2
  • Adam, 𝛽1 = 0.9, 𝛽2 = 0.999
  • 𝜖 = 1e−7
  • Steps = 6 × 10^5

Progress

  • Splitted Convolution Block is done.
  • Residual Block is done.
  • Mean shift layer is done.
  • Beta version of model is ready.

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SplitSR: An End-to-End Approach to Super-Resolution on Mobile Devices (Unofficial Implementation)

License:MIT License


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Language:Python 100.0%