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Questions tagged [gan]

GAN refers to Generative Adversarial Networks. Such networks is made of two networks that compete against each other. The first one generates new samples and the second one discriminates between generated samples and true samples.

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WGAN-GP: how to understand whether my networks are working as they are supposed to?

I am training a WGAN-GP. Is there any way to verify whether my networks are working as they are supposed to during training? I have no feeling about the outputs of my networks. I do not want to wait ...
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In which way GAN generator transforms the data(for transforming a noise to the data)?

I have the problem: I understood how GAN works in general, but I need information how it work detailed. The part I don't understand is how the random noise at input is transformed to data on the ...
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Predicting a signal based on other signals

I want to predict a signal based on other related signals, how would I go about doing this? My current approach is to do some feature extraction (in the time and frequency domain) on both the ground ...
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Is it right to argue that a testing dataset is not needed when evaluating the performance of a GAN?

For my degree final project I have been working on a GAN to solve a certain image enhancement task. The problem I’m currently working on has an extremely limited number of datasets due to the physical ...
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How do GANs learn category distributions

I'm currently getting more into the topic of GANs and Generating Models. I've understood how the Generator and Discriminator work together in optimization to generate synthetic samples. Now I'm ...
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CycleGAN: Both losses from discriminator and generator drop fast, after 100 epochs outputs blurred original image

I'm trying to train a 3D Cycle-GAN on medical image synthesis, more specifically CT to MR. Currently I'm using a 3-Layer Discriminator and a 6 layer UNetGenerator borrowed from the official CycleGAN ...
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proper solution to synthesize nailart on hand picture

I'm trying to synthesize nailart on hand picture. Next 3 steps are what I'm trying to do. take hand pictures select options like color, cubic .. etc synthesize And the way I thought to solve this is ...
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Super Resolution GAN with different input image size

Good morning, I am trying to train a Super Resolution GAN. Following some materials on the web I managed to train a first SRGAN model. To do that I took some high resolution image (128x128 pixels) and ...
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Keras Backpropagation when Later Layers are Frozen

I am working on a project with facial image translation and GANs and still have some conceptual misunderstandings. In my definition of my model, I extract a deep embedding of my generated image and ...
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Can I use Variational Autoencoder/GAN for image manipulation?

I have a CT image with the tumor and the corresponding Radiotherapy image. I want to predict the CT-Image with the corresponding change. For my training, I do have input CT image, Radiation therapy ...
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Is there any papers on adaptive discriminator augmentation in 3D?

I am really impressed with the results of ADA in action. Currently I work with 2D data (normal png images) but I would like to train StyleGAN2 + ADA in 3D space. Is there any papers/implementations ...
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WGAN with simplest data

I want to train WGAN (pyTorch) to generate this simple data. Here below my generator and critic architechtures: ...
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Generation of similar images with a neural network

Are there some known neural networks that, given an input image, can generate a similar image, with the same topic? Example: input = a photo of a cat on a green tablecloth, output = a generated photo ...
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Affine transformation in Style gan

I'm reading Style GAN paper and in style gan, we are passing the vector "W" through "A". I didn't understand what exactly the "A" is doing. In paper, it's mentioned ...
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Predict sequence using seqGAN

I am trying to create a GAN model in which I am using this seq2seq as Generator and the following architecture as Discriminator: ...
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Image normalization and reverse normalization: colors lost on image generation (GAN)

I'm working on a Gan. Based on different papers, I use a Tanh activation function on the last layer of the generator. Which produces [-1,1] outputs. To make this coherent, I use image normalization ...
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RCNN to predict sequence of images (video frames)?

In the following work the authors apply a convolutional recurrent neural network (RNN) to predict the spatiotemporal evolution of microstructure represented by 2D image sequences. In particular, they ...
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Gan paper: sampling the distribution

In the Gan paper it is said page 3 Figure 1: "The lower horizontal line is the domain from which z is sampled, in this case uniformly. The horizontal line above is part of the domain of x. The ...
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Symmetry when using the Kantorovich-Rubinstein duality

In the WGAN-paper, an equivalent formulation of the Wasserstein distance is used. From my understanding, the Wasserstein distance is symmetric, but the version in paragraph 3 doesn't seem like it is. ...
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Latent Space/Vector of StyleGANv1

I was going through the paper titled "A Style-Based Generator Architecture for Generative Adversarial Networks". You can find this paper here. I have the following two doubts: The generator ...
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In my GAN model, the discriminator loss quickly descends to magnitudes of $10^{-4}$ while generator loss is at levels of 5+?

I am creating a Generative Adversarial Network (GAN) for generating artificial trading cards, but I am a complete novice in the field. The problem I'm consistently having is that my discriminator, ...
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Synthetic Tabular Datta

I have found many examples of GANs on github for generating synthetic tabular data. I am trying to emulate this google collab notebook for synthea data. https://colab.research.google.com/drive/...
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Connection between GANs and adversarial learning

Is there a connection between: "Adversarial Learning" (AL) and "Generative Adversarial Networks" (GANs)? Is it valid to say that GANs employ AL?
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Is it possible to have ACWGAN

We have ACGAN model where the vanilla or basic GAN architecture. But in the same way can we have ACWGAN and ACWGAN-GP architectures for specific class image generation?
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Random Noise in GANs

What does the "random input" from noise (random noise) mean in GANs? Let's say I want to synthesize data such as name, age, income etc.. Does my generator know the original data sets (and ...
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VQ-GAN understanding

I tried to understand how VQ-GAN works, but unfortunately I have not understood it. I tried to read some articles about it and watch a video. I believe a good and simple article will help me. You ...
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GAN that generates locally accurate results

I'm wondering if there are any resources for problems of the following nature: Instead of training a GAN on a bunch of different faces, train a GAN on a very small number of faces (even 1), and ...
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How to implement self attention Generator and Discriminator in Conditional Generative Adversarial Nets

We have a CGAN built with a generator and a discriminator built using neural networks. How can we change the code to implement the same logic using self attention generator and discriminators? Our ...
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Question on hinge loss for GANs

I'm currently experiencing some difficulty with the hinge loss optimizer for GANs. In the equation below, the discriminator is looking to minimize $L_D$ and the ...
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How to replace the clothes of person using GAN?

I have one source video, let us say if the person is standing or walking in the video, the person's clothes should swap with the destination image (contain the picture of any clothes). I would like to ...
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StarGAN How to test discriminator

I'm running the following code: https://github.com/taki0112/StarGAN-Tensorflow I have my model pretrained. After the training I want to run the discriminator function to check its accuracy. Assume ...
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How to train a GAN to generate categorical variable

I am trying to train a simple GAN to generate a categorical variable size, which takes discrete values between 1-100. I am looking for some tips or directions on ...
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When training a cGAN on a X (B/W image) to Y (RGB image) "paired" dataset, how much will slight differences in the images matter in terms of results?

Right now I am working on a colorization project with GANs, and had originally settled on using a CycleGAN because I considered structuring my dataset in an unpaired manner. I've since been able to ...
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GAN model with different optimization functions

Building GAN model contains the following steps: Build generator model, and choose ...
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DCGAN - advise on why the training is not working

Objective Seeking for suggestions and advice why the DCGAN training is not working. Task Train DCGAN to learn to generate CIFAR10-like images. Each CIFAR10 image has the shape (32,32,3) where (32x32) ...
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Understanding math notation in infoGAN paper

I'm reading this paper about mutual information in infoGAN infoGAN_paper_link and already have the code to run it. I pretty much found code for it which is fine and dandy except for the fact that I ...
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SAGAN - what is the correct architecture?

Hi, in the original paper the following scheme of the self-attention appears: https://arxiv.org/pdf/1805.08318.pdf In a later overview: https://arxiv.org/pdf/1906.01529.pdf this scheme appears: ...
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Is a multi-layer perceptron exactly the same as a simple fully connected neural network?

I've been learning a little about StyleGans lately and somebody told me that a Multi-Layer Perceptron, MLP, is used in parts of the architecture for transforming noise. When I saw this person's code, ...
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Question About Discriminator of CycleGan

The Discriminator of CycleGan outputs not just a single value to say that the image is real or fake.... But It outputs a grid of numbers (like 8X8 or 7x7), where each number says whether one patch of ...
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How does the GAN based prediction in K. Zhang et al. (2018) improve performance?

In Stock Market Prediction Based on Generative Adversarial Network by K. Zhang et. al, the authors feed financial data (X0...Xt) into an LSTM to predict Xt+1. Then, they evaluate whether the series (...
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Generative adversarial network error in training process

I'm trying to make GAN which will generate art from random noise. I rely on this article https://towardsdatascience.com/generating-modern-arts-using-generative-adversarial-network-gan-on-spell-...
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Channels in CNN/GAN

I found this article about art generation which uses GAN architecture to generate art. Let's move to part where we define our generator model. ...
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Using StyleGAN for generative design of aircraft

I haven't worked on a machine learning project in a year and now that I am in university I am trying again :) Anyway, the end goal is to create a GAN that can design aircraft. I was inspired by the ...
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Get data from intermediate layers in a Pytorch model

I was trying to implement SRGAN in PyTorch and I have to write a Content loss function that required me to fetch activations from intermediate layers for both the Generated Image & Original Image. ...
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How to Connect Convolutional layer to Fully Connected layer in Pytorch while Implementing SRGAN

I was implementing the SRGAN in PyTorch but while implementing the discriminator I was confused about how to add a fully connected layer of 1024 units after the final convolutional layer My input ...
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Improving the pix2pix Architecture for Sketch to Image Translation on a Dataset of Sketches of People to Photos of People

For a university project, I need to create a neural network that translates sketches of people into images. In order to implement such a neural network, I decided to implement a pix2pix GAN ...
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pix2pix GAN with Rectangular Image Dataset

I am currently working on a project (for university) which translates sketches of faces to images of this person. For implementing this, I decided to use a pix2pix GAN architecture. However, I have ...
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Using GANs to generate synthetic tabular data to improve supervised learning

One topic I see some people trying is using GANs to generate synthetic tabular data for supervised learning. Also as a way to oversample the minority class in a binary classification. For me creating ...
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How are pictures pre processed before being used as ML data

So I was watching this YouTube video So basically the professor used ML to generate random faces in order to create data for a Kaggle challenge. When I looked into the data file, I was expecting to ...
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When to use GAN over conventional sampling methods?

Let's say I have a dataset from a diabetes hospital which has 30000 Type 2 diabetes and 300 Type 1 diabetes patients. So this dataset has millions and millions of other data points like lab ...
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