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Fast_Portrait_Segmentation

Fast (aimed to "real time") Portrait Segmentation at mobile phone

This project is not normal semantic segmentation but focus on real-time protrait segmentation.All the experimentals works with pytorch.

I hope to find a effcient network which can run on mobile phone. Currently, successfull application of person body/protrait segmentation can be find in APP like SNOW&B612, whose technology is proposed by a Korea company Nalbi.

Models

  • Encoder : mobilenet_v2(os: 32)

    Decoder : unet(concat low level feature) use dilate convolution at different stage(d = 2, 6, 12, 18)

  • Encoder : shufflenet

    Decoder : skip connection (add low level feature)

  • esp_dense_seg[20][10][15][19]

  • Attention model is a potential module in the segmentation task. I use a very light residual-dense net as the backbone of the Context Path. The details about fussion of last features in Contxt Path is not clear in the paper(BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation).

Speed Analysis

TODO

Result Examples

TODO

References

papers