Skip to main content
OverflowAI is here! AI power for your Stack Overflow for Teams knowledge community. Learn more

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.

Filter by
Sorted by
Tagged with
0 votes
0 answers
9 views

Why does the TensorFlow docs use a different GAN generator loss?

As per the original paper that introduced GANs, the generator loss is given as: $$ L_{G} = L _{BCE}(\mathbf{\vec 0}, \mathbf{D}(\mathbf{G}(\mathbf{\vec z}))) = \log(1 - \mathbf{D}(\mathbf{G}(\mathbf{\...
Sagnik Taraphdar's user avatar
0 votes
0 answers
7 views

cGAN: Discriminator loss going to zero while Generator's going always up but the result is very good

I have a Conditional Generative Adversarial Network for Quantum State Tomography. The metrics I am monitoring during the training process are the losses and the Fidelity (the degree of similarity ...
Dimitri's user avatar
  • 23
1 vote
1 answer
31 views

How to ensure that the output of my generative model is uniform?

Generative models transform noise to data. However, is there a way to ensure the output of my generative model follows a specific distribution, say uniform? More concretely, applying a scalar function ...
Butters's user avatar
  • 21
0 votes
0 answers
7 views

DCGAN for mammograms

I'm currently working on a DCGAN with Wasserstein Distance Gradient Penalty (WGAN-GP) for mammograms. The target mammograms are in 4D, as I'm using SD VAE 1.4 to reduce the complexity. Each of the ...
Norhther's user avatar
0 votes
0 answers
11 views

Seeking ML Model Recommendations for Enhancing OCR on Corrupted Text Images

I am working on a project where I need to perform Optical Character Recognition (OCR) on text-based images. However, these images are corrupted in various ways (e.g., blurred, distorted, low ...
Nurbek Ss's user avatar
0 votes
1 answer
20 views

CGAN not getting conditioned properly. How to start debugging?

So I was trying to condition some images (10 classes) on corresponding EEG signals. However after traing, the CGAN is producing decent looking images but the images being produced simply do not ...
Maurya's user avatar
  • 26
0 votes
1 answer
17 views

Are the number of channels increasing with conv2d filter?

So, I've been looking into CycleGAN code from Kaggle written by Amy Jang and..... I came to this code where we are basically downsampling our supplied image which has an input size of [256, 256, 3]. . ...
Ayush Dave's user avatar
0 votes
0 answers
35 views

GAN/DC-GAN isn't converging

I've been trying to train a vanilla GAN(for MNIST) for a few days, and nothing works. I've tried a lot of different layers, hyperparameters, and more, but every time the discriminator's loss decreases(...
Complex's user avatar
0 votes
0 answers
11 views

Modify data from generator before sending to discriminator

I am trying to build a GAN, which will take in datasets of size (1, 1800) and generate me similar looking 1-D arrays. But, I want the generator to output an array of size (1, 400), which will be sent ...
Lucifer Williams's user avatar
0 votes
1 answer
33 views

Frechet Inception Distance (FID) score: is this suitable to measure quality of individual generated image or only for group of generated images?

If I want to measure the quality of the images generated from GAN, what metric should I use and any reference for it so that I can check how it's done? I was thinking of using Frechet Inception ...
Curious's user avatar
0 votes
0 answers
9 views

How to mask particular segment of images while training CycleGAN?

Say I am using a CycleGAN to generate Zebra from Horse. But for my case, there is also deer present in both of the images, and I don't want to change the deer from my input and keep them the same in ...
SrJ's user avatar
  • 858
0 votes
0 answers
111 views

Generator loss not decreasing while training GAN

I’ve been attempting to create a basic GAN to generate images using this database of flowers (https://www.robots.ox.ac.uk/~vgg/data/flowers/102/). I’ve spent a few days on this, and largely based my ...
Hozaifa Bhutta's user avatar
0 votes
0 answers
13 views

Data generation with correlated columns

I am working on a finance project where i have to work on a model that predicts the short term impact on the bonds market (on the Spreads yield) when a big trade happens based on it's duration, ...
AhYas02's user avatar
0 votes
0 answers
21 views

In the GAN objective function, why do we first do we first find the D(x) that maximizes the objective function and then maximise wrt the generator?

The GAN objective function is optimised like this: argmin(argmax(L(G,D))) where the argmax finds the D (Discriminator) that maximises L(G,D). Why is it not the other way around, i.e. argmax(argmin(L(G,...
thebasqueinterdisciplinarian's user avatar
0 votes
0 answers
21 views

How to train a VQ Gan Based on Pretrained Language and Image Encoder?

I have trained the dual encoder model (separate language and vision encoders) using the ideas here. However, this looks like an image look up model rather than an image generation model. What would ...
Della's user avatar
  • 335
1 vote
1 answer
17 views

gnet loss is increasing, while my dnet loss is decreasing, what is wrong with the GAN?

I am developing an MIT open source GAN to generate synthetic structured health data, in the standard FHIR format. I have a running GAN, and it is using 200,000 Synthea Patient FHIR resources to train....
FHIRFLY's user avatar
  • 11
0 votes
0 answers
27 views

Help with running topology GAN (TopoGAN)

Link: https://github.com/TopoXLab/TopoGAN-ECCV2020 Sorry if this is the wrong place to ask, but I've been looking for help on how to work this out for a long time as I don't have much experience in ...
fds-mqdwqmqkdwl's user avatar
1 vote
0 answers
43 views

Generator loss keeps increasing while discriminator keeps decreasing

I am trying to build a GAN to generate LEGO images however my generator is not working at all. I have tried changing the learning rates but it caused the loss to go even more higher, sometimes into ...
Abhinav Painuli's user avatar
1 vote
1 answer
197 views

timeGAN Model Retraining

I am using timeGAN from ydata-synthetic repo, and now question is about re-training the model. Suppose we have trained a model, say synth1, based on a certain ...
TripleH's user avatar
  • 157
0 votes
1 answer
43 views

Generate Synthetic Data Indicating Original data's Trend

I am using timeGAN from ydata-synthetic repo. Given a trained model synth, we generate synthetic data by: ...
TripleH's user avatar
  • 157
1 vote
1 answer
61 views

GAN Output Gradient Calculation

Loss function for discriminator, which needs to be maximized: -log(D(x)) + log(1-D(G(z))). Loss function for generator, which needs to be maximized: log(D(G(z))) What would the calculation of the loss ...
David's user avatar
  • 11
0 votes
1 answer
50 views

Improve image classification model with trained generator

Is it possible to improve an image classification model with a generator (trained class conditionally). (so this is same source/target distribution and same source/target task, so not domain ...
InKodeWeTrust's user avatar
1 vote
1 answer
143 views

Questions on reproducibility of TimeGAN results

I am playing the timeGAN model, using the example code from ydata-synthetic repo. To train the model, we used synth.train(stock_data, train_steps=50000) to ...
TripleH's user avatar
  • 157
1 vote
0 answers
39 views

What is the l2-norm of a scalar

What is the meaning of the l2-norm when dealing with scalar values? I'm assuming it would be the same thing as taking the absolute value. For context: I am trying to implement the clustering method ...
Droidenkiller's user avatar
1 vote
2 answers
202 views

Why is cycle consistency loss alone not sufficient to produce meaningful output?

Imagine an adaptation of CycleGAN, in which the discriminators were removed in lieu of using only cycle consistency loss. Well, it turns out that the original authors of Cycle Consistent Adversarial ...
Value_Investor's user avatar
1 vote
0 answers
46 views

In WGAN paper, why does clipping weights approximate Lipschitz function?

In Wasserstein GAN, it's explained that maximizing a certain formula over a set of K-Lipschitz functions approximates the 1-Wasserstein distance and they model the functions as NNs. That much I ...
znb's user avatar
  • 11
0 votes
1 answer
195 views

I'm Looking for dataset with Name, Father's Name, Mother's name, Age, Gender, Ethnicity, ~Birthplace [closed]

I am new to Data Science and I don't know where to find datasets, I Google searched, Asked ChatGPT and friends, but couldn't find what I was looking for. My project is to generate new names based on ...
JeX's user avatar
  • 1
0 votes
1 answer
724 views

Transpose Convolution Output Size

I have been learning GAN (Generative Adversarial Networks) lately and having a hard time understanding the output size for transpose convolution. Let's say I am using a Tensor of [1, 64, 1, 1] as an ...
pwnkit's user avatar
  • 47
0 votes
1 answer
375 views

How to build an image generation model for interior room design?

I want to build an image generator model of interior room design. This model should be able to generate an interior image of a living room/bedroom/hall/kitchen/bathroom. I have searched about it and ...
dark horse's user avatar
0 votes
0 answers
165 views

Getting error "Failed to find data adapter that can handle input" even after converting list to array

I am getting this error : ValueError: Failed to find data adapter that can handle input' I even changed the list to arrays but still the error keeps pooping up. This is the code: ...
Hemangi khatri's user avatar
0 votes
1 answer
115 views

GAN Generator Backpropagation Gradient Shape Doesn't Match

In the TensorFlow example (https://www.tensorflow.org/tutorials/generative/dcgan#the_discriminator) the discriminator has a single output neuron (assume batch_size=1). Then over in the training loop ...
rkuang25's user avatar
2 votes
0 answers
111 views

Diffusion Model without Text Prompt?

I hope I understand diffusion models well enough that this isn't too dumb of a question but... I'd like to (I think) augment a diffusion model to: At training time accept CT scan images, then apply an ...
ncf031's user avatar
  • 21
0 votes
1 answer
56 views

How to train encoder in BiGAN?

I have some difficulties training a BiGAN. In particular, the encoder seems not learning the map between the images x and the latent space z. I have the following encoder: ...
Pippo's user avatar
  • 1
0 votes
1 answer
22 views

How long is the generator pre-trained in SeqGAN?

I am reading up about SeqGAN and I am trying to understand the pretraining step better. The authors claim they want to maximize the Maximum Likelihood Estimation on the dataset S by pretraining the ...
postnubilaphoebus's user avatar
3 votes
1 answer
130 views

Why is it an advantage "that Markov chains are never needed" to obtain gradients?

In the original GAN (Generative Adversarial Network) paper, Generative adversarial networks by I. Goodfellow, J. Pouget-Abadie, M. Mirza et. al. they state an advantage of the GAN is "that Markov ...
p1unge's user avatar
  • 33
1 vote
1 answer
180 views

Confusion on DCGAN generator project & reshape

I've been recently studying DCGAN. I tried following implementation from the pytorch.org DCGAN tutorial and found that it (seemingly) lacks project & reshape layer, which is present in the diagram:...
Quasar-Kim's user avatar
1 vote
1 answer
84 views

Where is the VGG in Cartoongan?

When I read through the paper of Cartoongan [CartoonGAN: Generative Adversarial Networks for Photo Cartoonization], I was so confused about where is vgg located in the entire network. Based on the ...
sss's user avatar
  • 13
0 votes
2 answers
1k views

Why is my DCGAN not converging?

I'm training a tf DCGAN on the MVTec hazelnut dataset and I found some difficulties. The problem is that after a lot of epochs the generate does not produce some quality images. My model is the ...
Pippo's user avatar
  • 1
2 votes
0 answers
57 views

Minor error in Ian Goodfellow's GAN optimality proof

I've been thinking of a part of the proof of the optimality of GANs from the original paper, and I can't manage to solve what seems to be an error. The paper states that the maximum of the function $y ...
J. P. C.'s user avatar
1 vote
0 answers
61 views

Why is my GAN diverging?

I am trying to train a GAN related to this project. At ~100k steps, the discriminator's fake loss suddenly went to 0, and real loss increased very high. (Can look at the plots below). What could be ...
Tejaswini 's user avatar
0 votes
0 answers
21 views

Do we know why GAN-based data augmentation works?

Although I've seen many examples of GAN-generated synthetic data greatly improving the performance of models, I struggle to understand how this is possible. Say we are training a classifier $h$ to ...
Isaac Wasserman's user avatar
1 vote
0 answers
7 views

Constrain GAN so the subject is always the same

I want to build a face GAN, but I want to be able to control the 'camera angle' of the generated image, and I also want the subject (the generated face) to be the same every time. If the above is ...
Karric's user avatar
  • 113
1 vote
0 answers
15 views

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 ...
Pavlo's user avatar
  • 11
1 vote
0 answers
22 views

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 ...
arturo salmi's user avatar
1 vote
0 answers
286 views

Super Resolution GAN with different input image size

I am trying to train a Super Resolution GAN. Following some materials on the web I managed to train the first SRGAN model. To do that I took some high-resolution images (128x128 pixels) and downscale ...
MattiaMartinelli's user avatar
0 votes
0 answers
61 views

WGAN with simplest data

I want to train WGAN (pyTorch) to generate this simple data. Here below my generator and critic architechtures: ...
simpler's user avatar
0 votes
0 answers
161 views

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: ...
ksohan's user avatar
  • 53
0 votes
1 answer
450 views

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 ...
Bouji's user avatar
  • 103
2 votes
1 answer
488 views

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 ...
Betelgeuse's user avatar
0 votes
1 answer
76 views

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 ...
Bouji's user avatar
  • 103

1
2 3 4 5