Diffusion Models Beat GANs on Image Synthesis
GPTKB entity
Statements (22)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:academic_journal
|
| gptkbp:arXivID |
2105.05233
|
| gptkbp:author |
gptkb:Prafulla_Dhariwal
Alexander Nichol |
| gptkbp:bench |
gptkb:CIFAR-10
gptkb:ImageNet |
| gptkbp:citation |
high
|
| gptkbp:field |
gptkb:machine_learning
computer vision |
| gptkbp:language |
English
|
| gptkbp:method |
empirical comparison of diffusion models and GANs
|
| gptkbp:plotSummary |
diffusion models achieve higher FID scores than GANs
|
| gptkbp:proposedBy |
diffusion models outperform GANs on image synthesis benchmarks
|
| gptkbp:publicationDate |
2021
|
| gptkbp:publisher |
gptkb:arXiv
|
| gptkbp:topic |
gptkb:generative_adversarial_networks
diffusion models image synthesis |
| gptkbp:url |
https://arxiv.org/abs/2105.05233
|
| gptkbp:bfsParent |
gptkb:NeurIPS_2022
|
| gptkbp:bfsLayer |
7
|
| https://www.w3.org/2000/01/rdf-schema#label |
Diffusion Models Beat GANs on Image Synthesis
|