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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How can my Pytorch based GAN output pure B&W with no grayscale?

My goal is to create simple geometric line drawings in pure black and white. I do not need gray tones. Something like this (example of training image): But using that GAN it produces gray tone images....
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Database augmentation using Sobel filter (aka gradient)

I'm working in PyTorch and to improve a ProGAN training I'm augmenting a database by calculating, for each image, the horizontal and vertical gradient via the Sobel operator. Do you have any reading ...
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LOGICS: GAN with image as input instead of a noise vector

i am having an idea for a single-class classifier. I don't know if this is a logical "short circuit", though. The idea is the following: Instead of a noise vector, i use a "noise-image" as input for ...
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340 views

Train a GAN on “before and after” images of dental surgeries [closed]

I want a GAN to train on "before and after" images of dental surgeries; so that it can generate "after" pictures for fresh patients. Input images are like these: https://img.webmd.com/dtmcms/live/...
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Is the hyperbolic tangent function a solution to the weight clipping problem of WGAN?

Instead of clipping to the range [-c,c] why not smoothly map into the range [-c,c] by using c*tanh(w) ? This would guarantee the Lipschizt constant is no greater than c. The problem I am talking ...
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How can I know my GAN does converge?

I am training my GAN, and by looking at the loss curves of the generator and discriminator, I think I am going on the right way because from this blog, my curves look reasonable: A stable GAN will ...
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Picking a model to go ahead with for a WGAN

I have been trying to train a model using WGAN loss functions, working different learning rates to choose my hyper parameters based on advice. I was told to try looking into keeping everything simple ...
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GAN training the average of my train data

I have been training a GAN with 1D convolutional layers on sinus functions. However if I start varying my sinus (random amplitude for example), the model generates only the average of the random range....
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Inception Score (IS) and Fréchet Inception Distance (FID), which one is better for GAN evaluation?

IS uses two criteria in measuring the performance of GAN: The quality of the generated images, and their diversity based on the entropy of the distribution of synthetic data. On the other hand, FID ...
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25 views

Generator losses in WGAN and potential convergence failure

I have been training a WGAN for a while now, with my generator training once in every five epochs. I have tried several model architectures(no of filters) and also tried varying the relationship with ...
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Solve an equation using machine learning [closed]

Imagine we have the following equation: y=xz. We have y but not other ones. Note that y is like a matrix and we could as many sample we want. It is the values obtained from sensors. This means it ...
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GAN loss suddenly explodes and model breaks

Almost every time I've tried to train a DCGAN using keras I find that the loss suddenly skyrockets and the model completely stops improving. I find this happens regardless of what combination of loss ...
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What would be a good loss function to penalize big differences and reward small ones, but not in a linear way?

I have an image with the differences between 2 other images. Concentrations of black pixels mean similar regions between the images, whereas, white values highlight differences. Thus I want a ...
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GAN generator producing distinguishable output

I am trying to train a special type of GAN called a Model-Assisted GAN (https://arxiv.org/pdf/1812.00879) using Keras, which takes as an input a vector of 13 input parameters + Gaussian noise, and ...
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29 views

GAN: Discriminator converges, generator learns almost nothing

In my GAN, the discriminator loss goes down steadily, while the generator loss oscillates / does not converge. I suspect this is due to the vanishing gradient problem. Theory: as the discriminator ...
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CycleGAN: Generator losses don't decrease, discriminators get perfect

So I´m training a CycleGAN for image-to-image transfer. The problem is: while the discriminator losses decrease, and are very small now, the generator losses don't decrease at all. The generator ...
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Does it make sense to do train test split when trainning GANS?

For normal supervised learning the dataset is split in train and test (let's keep it simple). Generative Adversarial Networks are unsupervised learning but there is a supervised loss function in the ...
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ways to implement multiple discriminators for GAN?

I'm tyring to build TTS system using GAN and was wondering if it's possible to build it using multiple discriminators and if I can, can you also explain how to? I'm building it using Keras.
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Metric to evaluate words generated by Neural Network

I have this task at hand and I would be grateful for some directions. Perfectly not the final solution as I would like to do it myself. Let's say I need to create new fruit names based on existing ...
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Generative Model for learning Periodic solutions 3-body/N-body problems

I am tasked with finding research where a GAN or any other generative model is used to generate new shapes of 3-bodies moving under the influence of each others' gravitational pull, in a periodic ...
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Using a GAN discriminator as a standalone classifier

The goal of the discriminator in a GAN is to distinguish between real inputs and inputs synthesized by the generator. Suppose I train a GAN until the generator is good enough to fool the ...
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One-hot encoding to embedded vector - BigGAN

I am trying to replicate a BigGAN architecture in Tensorflow https://arxiv.org/pdf/1809.11096.pdf but fail to understand exact nature of inputs. BigGAN generator has 2 inputs, noise ...
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1answer
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GAN loss function [closed]

I am new to deep learning field and I want to synthesize as accurate as it can be, can someone tell me how to construct loss function for such model, any answer will be a great help please do not ...
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Spatial deformation in medical MR images

HI fellows I hope everyone will be good I just want to ask that what is spatial deformation and I want to apply this spatial deformation on medical MR images any answer will be helpful. Thanks and ...
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1answer
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How different should discriminator be from generator in GAN

When training a GAN, the generator $G$ strives to fool the discriminator $D$, while $D$ attempts to catch any output generated $G$ and isolate it from a real data point. They grow together training in ...
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Is it possible to use Generative Adversarial Networks (GANs) for text classification?

I am working on the classification of fake and real news. I did use a CNN Model for this problem and got satisfactory results. But, I was just wondering if it's at all possible to use any type of GAN ...
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Error: An operation has `None` for gradient with categorical_crossentropy

I am trying to train my discriminator network using Keras with TensorFlow backend. The network is meant to classify the input into one of the 9 output labels. I am passing a 2D input (height, width, ...
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Do I need to train a separate DeepFake model for every input person?

I would like to create a deep fake model of a specific person (we will call him Steve). I would then like to be able to upload a video of any random person and swap their face with Steve's. So far I ...
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Conceptual help generating a text adventure game using a GAN

I have built a playable dungeon crawler game that lets a character progress through a series of randomly generated rooms filled with doors, chests, stairs, etc. Ideally, I would be able to display a ...
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Using a DCGAN to create an intrusion detection system

The TL;DR of my question is how do you write a discriminator and generator of a DCGAN in pytorch to accept a csv file instead of an image? I am attempting to partial recreate an experiment from the ...
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Generative Adversarial Networks - The simplest possible examples

I'm looking for the simplest possible examples of GANs. What would be simple yet illustrative examples with, say, univariate data and in which both the generator and the discriminator are as simple as ...
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What is a latent space vector?

I do not understand this about GANs. Apparently the Generator is supposed to receive a latent space vector as its input. Yet I couldn't find an example of how I can implement it in Pytorch. This is a ...
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152 views

Custom Loss function - An operation has `None` for gradient

i want to write my own loss function to train a GAN in Keras. The Generator should learn to write word images. Therefore i use a Discriminator and a Text Recognition. The Generator should learn from ...
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Why does the generator produce output in a different scale than the training sample?

I am currently trying to train a GAN (based on proGAN) to produce images in a Vaporwave-style which is quite distinct. The results so far have been underwhelming, which I suspect might be due to a ...
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How to generate sports tracking data using deep learning?

Data: I have a 2D Numpy array that contains tracking data for football. Each row has the (x,y) coordinates for all players + the ball. That's 22 players and 1 ball = 46 columns. The frequency is 0.1 ...
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1answer
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Is it faster and better to train a GAN on just one digit as opposed to the whole mnist dataset?

When going through an introductory GAN tutorial to generate mnist like handwritten digits I wondered whether the systematic variance in the training data due to the different digits makes the model ...
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Gan in Keras - You must feed a value for placeholder tensor

i have a problem with the training of my GAN. I get the following error message: ...
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Is this interpretation of spectral normalisation mathematically correct?

Hello everyone, this is my first post. I was thinking about the mathematical interpretation for spectral normalization in neural networks the other day, and I came up with an explanation that feels ...
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How Cycle GAN translates between very different objects?

I'm trying to understand how the popular CycleGAN responds if the objects to be translated between are very different (horse and map or house and apples). All of the examples appear to be translating ...
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How to generate several elements on image with input parameters

For example, i need to generate circles. I have dataset of images with non-intersecting circles and can generate random circles with DCGAN, but each circle has a different diameter. So I need to ...
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1answer
184 views

WGAN-GP slow critic training time

I am implementing WGAN-GP using Tensorflow 2.0, but each training iteration of the critic is very slow (about 4 secs on my CPU, and somehow 9 secs on Colab GPU). Is WGAN-GP usually this slow or ...
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How to grasp the full entropy of the distribution we want to model in GAN

In pix2pix GAN paper( https://arxiv.org/abs/1611.07004), authors found that the noise vector and the dropout are not efficient in grasping the full entropy of the data distribution we want to model. ...
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InfoGAN Learning Latent Categorical Code

While reading the InfoGAN paper and implement it taking help from a previous implementation, I'm having some difficulty understanding how it learns the discrete categorical code. The implementation ...
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Different optimizers for generator and discriminator in GAN

I've seen an advice about GAN implementation, that there should be different optimizers for generator (G) and discriminator (D). As I understand, it depends on how fast each model (G and D) ...
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Validation of Images generated using DCGAN

I have trained a Deep Convolutional Generative Adversarial Network(DCGAN) model and generated some images. Now, I need to validate these images if generated images ...
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GAN for illumination removal

i'm reading a paper using GAN to process illumination in image: https://ieeexplore.ieee.org/document/8545434. In the paper, the author mentioned using the SSIM loss for quality evaluation of the ...
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392 views

DC GAN with Batch Normalization not working

I'm trying to implement DC GAN as they have described in the paper. Specifically, they mention the below points Use strided convolutions instead of pooling or upsampling layers. Use only one fully ...
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Which service could I use to train my networks?

My laptop's Intel i7 3630QM 2.4GHZ, 8Gb RAM and GXForce 670M are clearly not sufficient... By reading some papers, I've written an SRGAN with Python Keras. At runtime there is no error but training ...
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SRGAN Generator Architecture: Why is it possible to do this elementwise sum?

Consider the first residual block. Its first convolution layer takes in inputs: THe PRELU's output 64 filters(64 outputs) each one being 3*3 with a stride of (1 ; 1) So I think that the output of ...