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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CycleGAN: Generator model only outputs very small values

So I'm trying to train a CycleGAN for image-to-image translation. The problem is my generator only outputs very small values, around 0 +- 5e10-6. Instead, it should output values between 0 and 1 (e....
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RuntimeError: CUDA out of memory. Tried to allocate 20.00 MiB

I'm trying to make a GAN for generating pictures using this code: https://github.com/abhinav3/Udacity-DCGAN-FaceGeneration/blob/master/dlnd_face_generation.ipynb I'm doing this learning on GPU. The ...
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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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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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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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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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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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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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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 ...
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How and Why to rescale image range between [0,1] and [-1,1]

I am trying to implement model described in Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network in which author says in section 3.2 that We scaled the range of the ...
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How to compute Frechet Inception Score for MNIST GAN?

I'm starting out with GANs and I am training a DC-GAN on MNIST dataset. The two metrics that are used to evaluate GANs are Inception Score (IS) and Frechet Inception Distance (FID). Since Inception ...
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Why does discriminiator accuracy falls to 0%, and is there a fix around this?

I am training a Vanilla-GAN(or original GAN 2016) on a pokemon dataset https://www.kaggle.com/kvpratama/pokemon-images-dataset, for few epochs the discriminator has 100% accuracy over the real ...
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How can one be assured that generative models are not memorizing dataset, and that they will generate an unique image outside of dataset?

If all GAN can do is capture the probability distribution of the dataset, then shouldn't they be similar to handing out images from the dataset? How can we verify that the images that they generate ...
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What does this symbol means, what operator is it?

I am confused about the $E_{x\sim P_{data}(x)}$, what does $E$ means here. I cannot find an appropriate answer on the internet, and hence I am trying data science stack exchange. Please help.
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Are mainstream pre-trained models useful as discriminators?

In the context of GANs I see many papers designing new discriminator networks. I'm curious about the usefulness of designing discriminators as modified versions of mainstream models like Inception, ...
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Thresholding in intermediate layer using Gumbel Softmax

In a neural network, for an intermediate layer, I need to threshold the output. The output of each neuron in the layer is a real value, but I need to binarize it (to 0 or 1). But with hard ...
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Problem regarding designing the generator function

I am implementing the paper Perceptual GAN for small object detection. The design is described by the picture given below. I have used Transfer Learning concept and used a pretrained model inside the ...
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Examples of using GANs to sort numbers?

Does anyone know of any publicly available GAN implementations to sort numbers with? As in, the input to the generator is an unordered sequence of numbers, and the goal of the generator is to output ...
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How discriminator knows if the image is real or fake at the initial phase?

If the discriminator and generator in GAN learn together, How the discriminator knows whether the image is real or fake in the initial phase of training? Does the discriminator need to get trained ...
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Comparsion between DCGAN and WGAN

What is the main architectural difference between DCGAN and WGAN? For which problems each models can be more useful than the other one?
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what is the main difference between GAN and autoencoder?

what is the main difference between GAN and other older generative models? what were the characteristics of GAN that made it more successful than other generative models?
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Training neural network to generate realistic terrain

I've recently had an idea to create a tool that makes it easier for environment artists to generate highly realistic terrain for video games. I've seen approaches using GANs and I'm familiar with the ...
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issues related to implementation of the paper 'Perceptual GAN for small object detection'

I am trying to implement the perceptual gan network using keras as backend. I am new in the field of GAN, can anyone provide me the model for perceptual GAN in keras backend
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Issues related to the code for ROI pooling from the feature map

I am trying to do ROI pooling on the feature map obtained from the VGG layers but I don't know how to code this layers. Can anybody help me out? Here is my VGG layers: ...