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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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 ...
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Why does this cGAN model perform poorly when trained on a different machine?
I was sent a cGAN model python file from a friend + the dataset he used to train this model. For him, the model trained succesfully & was able to generate very accurate images. These were his ...
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Interpret loss of WGAN
I have been working with WGAN-GP to produce text.
However, I have some issues interpreting the loss functions.
First of all, the loss seems awfully small. After the first 300 batches (which translate ...
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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 ...
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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 ...
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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 ...
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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 ...
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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:
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Help to find strategy of transfer learning with a conditional pix2pix model
so I trained a similar model to pix2pix GAN to generate output images. I condition my model on three different types:
there are 120 input images and 2 parameters (param_1, param_2). For each parameter,...
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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 ...
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Understanding the Pulse Extractor in this paper
I'm reading this paper about a neural vocoder for singing synthesis:
https://arxiv.org/pdf/2210.12740.pdf
I've implemented vocoders before, but this one discusses a novel pulse extractor:
T[i] is ...
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Which combination would be more beneficial : Resnet-50 and SVM or Resnet-18 and GANs?
I'm trying to compare the two methods that were used for COVID-19 detection.
Given that both these methods have approximately the same accuracies
which method according to you would be more beneficial(...
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GAN architectures for handling big size images
I am trying to generate new images in order to improve the number of samples in a dataset.
I have noticed that the majority of the GANs are trained with quite small images. For example, ...
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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 ...
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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:
...
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Role of Expectation and (1-y) in GAN Equation
I am reading about the GAN equation and I was wondering why Expectation was used twice? As of my (lack of) understanding, Expectation is a generalization of the mean because there is an infinite ...
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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 ...
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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 ...
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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:...
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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 ...
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What is the difference between a perfect image-GAN and duplicating the photo a billion times and having auto-photo-shop?
What is the difference between a perfect image-GAN and duplicating the photo a billion times and having automatic Adobe photoshop to do style-transfer/deep-dream?
I can't tell you what the advantage ...
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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 ...
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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 ...
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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 ...
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Is GAN better than DBNs?
I understand that they are different models and work differently, but they are both generative models and can both be used to do feature learning and classification. Is GAN most of the time better ...
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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 ...
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GAN - discriminator loss remains at a constant value while the generator loss decreases?
I am building my first GAN network, and I noticed that sometimes the discriminator loss remains at a constant value while the generator loss decreases.
I couldn't find an explanation - if the ...
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Why is FID so popular for evaluating GANs and other generative models?
The FID seems to be the most popular evaluation metric for GANs and other generative models. Why is it so popular? It seems to have some obvious issues, such as the assumption of Gaussian ...
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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 ...
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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
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 ...
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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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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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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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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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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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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 ...
