Methods › Computer Vision › Generative Adversarial Networks › Relativistic GAN
Relativistic GAN
Introduced by Alexia Jolicoeur-Martineau in The relativistic discriminator: a key element missing from standard GAN
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
A Relativistic GAN is a type of generative adversarial network. It has a relativistic discriminator which estimates the probability that the given real data is more realistic than a randomly sampled fake data. The idea is to endow GANs with the property that the probability of real data being real (D(xᵣ)) should decrease as the probability of fake data being real (D(x_f)) increases.
With a standard GAN, we can achieve this as follows. The standard GAN discriminator can be defined, in term of the non-transformed layer C(x), as D(x) = sigmoid(C(x)). A simple way to make discriminator relativistic - having the output of D depend on both real and fake data - is to sample from real/fake data pairs x̃ = (xᵣ, x_f) and define it as D(x̃) = sigmoid(C(xᵣ) − C(x_f)). The modification can be interpreted as: the discriminator estimates the probability that the given real data is more realistic than a randomly sampled fake data.
More generally a Relativistic GAN can be interpreted as having a discriminator of the form a(C(xᵣ)−C(x_f)), where a is the activation function, to be relativistic.
Papers archive 2025-07-28
6 shown of 6, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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The GAN is dead; long live the GAN! A Modern GAN Baseline 9 Jan 2025 · 1 repository · arXiv:2501.05441Syntology ran 9 of 11 samples · 2 unverified · 11 pointer-only (licence)
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A Three-Player GAN for Super-Resolution in Magnetic Resonance Imaging 24 Mar 2023 · 0 repositories · arXiv:2303.13900
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Improve GAN-based Neural Vocoder using Pointwise Relativistic LeastSquare GAN 26 Mar 2021 · 0 repositories · arXiv:2103.14245
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UU-Nets Connecting Discriminator and Generator for Image to Image Translation 4 Apr 2019 · 0 repositories · arXiv:1904.02675
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ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks 1 Sep 2018 · 46 repositories · arXiv:1809.00219Syntology ran 8 of 44 samples · 36 unverified
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The relativistic discriminator: a key element missing from standard GAN 2 Jul 2018 · 10 repositories · arXiv:1807.00734Syntology ran 1 of 9 samples · 8 unverified · 2 pointer-only (licence)
Tasks archive 2025-07-28
9 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Image Generation | 3 |
| Generative Adversarial Network | 2 |
| Image Super-Resolution | 2 |
| Super-Resolution | 2 |
| Decoder | 1 |
| Face Hallucination | 1 |
| Image-to-Image Translation | 1 |
| Translation | 1 |
| Video Super-Resolution | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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