Answers.Body: <p>The idea of taking an additional label as input sounds like a conditional generative adversarial network (cGAN). Within a conditional GAN both the discriminator and the generator are conditioned on extra information provided through a label. The idea was first introduced in this <a href="https://arxiv.org/pdf/1411.1784.pdf" rel="nofollow noreferrer">paper</a>.</p>
  <p>This image from this <a href="https://www.researchgate.net/publication/338979046_An_analysis_of_generative_adversarial_networks_and_variants_for_image_synthesis_on_MNIST_datasetnicely" rel="nofollow noreferrer">paper</a> nicely highlights how a conditional GAN differs from a standard GAN:</p>
  <p><a href="https://i.sstatic.net/8szrG.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/8szrG.png" alt="GAN_comparison" /></a></p>
  <p>Such an architecture would likely also be suitable to be conditioned on image rotations.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-12-27T17:53:43.017Z
Answers.LastActivityDate: 2022-12-27T17:53:43.017Z
Answers.UserDisplayName: Mariusmarten
Body: <p>It seems to me that the Generative Adversarial Networks have a practical issue when trying to reproduce some of their output images</p>
  <p>For example, as you can see <a href="https://www.youtube.com/watch?v=oIzwe_MOeQI&amp;t=1057s" rel="nofollow noreferrer">https://www.youtube.com/watch?v=oIzwe_MOeQI&amp;t=1057s</a> seems to generate shape and background changes as it changes rotations.</p>
  <p>Can any of the StyleGANs be convinced to take an image of a car, along with some sort of key that says how it is rotated then consider that when the trained model is generating?</p>
  <p>Obviously, it might be a substantial effort to label the data, but I'm curious if it's been done in a well-published fashion.</p>
  
Tags: <generative-adversarial-networks><style-transfer>
Title: Can any GAN's utilize labels in their datasets while they are training?
UserDisplayName: user1833028
ThreadText: # Can any GAN's utilize labels in their datasets while they are training?
  
  (Asked by: username_0 on 2022-12-26)
  
  It seems to me that the Generative Adversarial Networks have a practical issue when trying to reproduce some of their output images
  
  For example, as you can see <https://www.youtube.com/watch?v=oIzwe_MOeQI&t=1057s> seems to generate shape and background changes as it changes rotations.
  
  Can any of the StyleGANs be convinced to take an image of a car, along with some sort of key that says how it is rotated then consider that when the trained model is generating?
  
  Obviously, it might be a substantial effort to label the data, but I'm curious if it's been done in a well-published fashion.
  
  **Tags:** generative-adversarial-networks, style-transfer
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2022-12-27. Score: 2
  
  The idea of taking an additional label as input sounds like a conditional generative adversarial network (cGAN). Within a conditional GAN both the discriminator and the generator are conditioned on extra information provided through a label. The idea was first introduced in this [paper](https://arxiv.org/pdf/1411.1784.pdf).
  
  This image from this [paper](https://www.researchgate.net/publication/338979046_An_analysis_of_generative_adversarial_networks_and_variants_for_image_synthesis_on_MNIST_datasetnicely) nicely highlights how a conditional GAN differs from a standard GAN:
  
  [![GAN_comparison](https://i.sstatic.net/8szrG.png)](https://i.sstatic.net/8szrG.png)
  
  Such an architecture would likely also be suitable to be conditioned on image rotations.
  
  
  ---
  
  