Deep Convolutional Food Styling

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recipes and photos by users

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5VSJOH5FTU Generative Adversarial Learning Generator Discriminator ( %

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%FFQ $POWPMVUJPOBM (FOFSBUJWF "EWFSTBSJBM /FUXPSLT

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%PXOTBNQMJOH features or small resolution image convolutional layer or layers RGB image input output

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6QTBNQMJOH upsampling CNN layer or layers RGB image features or small resolution image input output

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&ODPEFS%FDPEFS D E image in Decoder Encoder image out feature space

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'VMMZ$POOFDUFE $MBTTJpFS YES NO classes data or features also called “Dense”   or “Linear” layer

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Generator Discriminator G MPPLTMFHJU UPUBMMZTIPQQFE D

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G SFBM GBLF D D(G(noise)) ˠ real (FOFSBUPSUSBJOJOH Discriminator acts as the teacher

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G SFBM GBLF D SFBM GBLF D D(G(noise)) ˠ fake D(photo) ˠ real %JTDSJNJOBUPSUSBJOJOH Generator provides negative examples

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https://www.youtube.com/watch?v=9reHvktowLY

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https://github.com/tatsuyah/CycleGAN-Models

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(FOFSBUPS transformation network https://arxiv.org/abs/1603.08155

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TVCUMF WJWJE … TVCUMF WJWJE %JTDSJNJOBUPS fully convolutional judges patches   of the input image https://arxiv.org/abs/1603.08155

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"EWFSTBSJBM-PTT X F G Y TVCUMF WJWJE TVCUMF WJWJE … TVCUMF WJWJE TVCUMF WJWJE … X(F(low_score)) ˠ classify as high_score Y(F(high_score)) ˠ classify as low_score

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https://snappygoat.com

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