2023-Q1-AI 19. CycleGAN

 

19.1. Materials / Video 🔴 5 Jun 2023, 19:00

Video: https://youtube.com/live/EUy3JqHVQTU?feature=share

Jamboard: https://jamboard.google.com/d/1Ihbq4z-TQWoHH_7spW9Q9fJt0z2tVfU-VFAPtQ2MMrI/edit?usp=sharing

Paper: https://arxiv.org/pdf/1703.10593.pdf


19.2. Implementēt CycleGAN

Implement CycleGAN based on instructions in 19.1

Template: http://share.yellowrobot.xyz/quick/2023-5-31-F72F1C44-8785-4680-9956-E7E34B00CC5E.zip

Iesniegt ekrānšāviņus ar labākajiem rezultātiem un programmas pirmkodu.

 

19.3. Mājasdarbs - Pievienot UNet Pix2Pix ģeneratoru

Implementēt Ģeneratora arhitektūru Pix2Pix, izmantojot pētījumu: https://arxiv.org/abs/1611.07004

Implementēt Summer2Winter Yosemite datu kopu https://www.kaggle.com/datasets/balraj98/summer2winter-yosemite

Iesniegt ekrānšāviņus ar labākajiem rezultātiem un programmas pirmkodu.

 


 

 

Video / Jamboard

Jamboard iedotas tiesības: vecins.valters@gmail.com

Video RTMP key: ea11-mrgb-4jg2-4ajc-d4hr

Kods iepušots GIT

 

Iepriekšējā gada video

 

Video: https://youtu.be/9iEaQMn_5fc

Jamboard: https://jamboard.google.com/d/1t4I-Ow2nPsjABaiD2Qd8z_auo3bRkGZTFX5f3nmXSqI/edit?usp=sharing

 

 


 

Būtu labi pārtaisīt uz horse2zebra dataset (Aigai bija labi apmācīts, Reinis arī pārziana)

 

Hoses to zebras source code:

https://www.kaggle.com/code/balraj98/cyclegan-translating-horses-zebras-pytorch

 

Good material: https://towardsdatascience.com/cycle-gan-with-pytorch-ebe5db947a99

https://blog.jaysinha.me/train-your-first-cyclegan-for-image-to-image-translation/

nn.ReflectionPad2d(3),

https://www.machinecurve.com/index.php/2020/02/10/using-constant-padding-reflection-padding-and-replication-padding-with-keras/

 

image-20230531181206297

 

img

image-20230531181009553

Attīstība:

  1. DTN-GAN

  2. ⚠️ Pix2Pix, PatchGAN => UNet architecture piespiež saglabāt aptuvenas features (Parasts GAN ar UNet prior)

    • ⚠️ “PatchGAN” classifier, which only penalizes struc- ture at the scale of image patches

    • Markov random field -> independence separated by patch diameter

    • https://arxiv.org/pdf/1611.07004.pdf

  3. LSGAN - https://arxiv.org/pdf/1611.04076v3.pdf

    1. Alternative to WGAN

  4. CycleGAN

    1. https://arxiv.org/pdf/1703.10593.pdf

  5. RecycleGAN - Temporal Information in Loss

  6. BicycleGAN - VAE tipa GAN - nav saistīts ar RecycleGAN un CycleGAN

  7. Better CycleGAN

    1. Same discriminator 3 classes! https://ssnl.github.io/better_cycles/report.pdf

image-20220106185840876

 

LSGAN image-20220106205959028

 

Pix2Pix - PatchGAN Discriminator (pa labi full Image GAN vs PatchGAN)

image-20220106191119742

 

Pix2Pix infilling task image-20220106190533129

Pix2Pix GAN -> UNet image-20220106190335914

 

RecycleGAN paper: CycleGAN mode collapse - pa vidu obama - mainās viens pikselis, kurš iekodē informāciju.

we get better outputs with our approach combining the spatial and temporal constraints.

image-20220106191322398

 

BicycleGAN: Z injection

image-20220106191830718

image-20220106191853410

image-20220106192242972

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