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update citations to match the linked whitepaper #3127

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Nov 10, 2023
Merged

update citations to match the linked whitepaper #3127

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1d0e9bc
update citations
djwadhwa Nov 10, 2023
805ba72
use original submission year
djwadhwa Nov 10, 2023
fe8b512
Merge branch 'master' into fix-whitepaper-citations
vfdev-5 Nov 10, 2023
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Merge branch 'master' into fix-whitepaper-citations
vfdev-5 Nov 10, 2023
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2 changes: 1 addition & 1 deletion examples/super_resolution/README.md
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Expand Up @@ -2,7 +2,7 @@

ported from [pytorch-examples](https://github.com/pytorch/examples/tree/main/super_resolution)

This example illustrates how to use the efficient sub-pixel convolution layer described in ["Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network" - Shi et al.](https://arxiv.org/abs/1609.05158) for increasing spatial resolution within your network for tasks such as superresolution.
This example illustrates how to use the efficient sub-pixel convolution layer described in ["Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network" - Shi et al. 2016](https://arxiv.org/abs/1609.05158) for increasing spatial resolution within your network for tasks such as superresolution.

```
usage: main.py [-h] --upscale_factor UPSCALE_FACTOR [--crop_size CROPSIZE] [--batch_size BATCHSIZE]
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4 changes: 2 additions & 2 deletions ignite/metrics/gan/fid.py
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Expand Up @@ -62,11 +62,11 @@ class FID(_BaseInceptionMetric):
where :math:`\mu_1` and :math:`\sigma_1` refer to the mean and covariance of the train data and
:math:`\mu_2` and :math:`\sigma_2` refer to the mean and covariance of the test data.

More details can be found in `Heusel et al. 2002`__
More details can be found in `Heusel et al. 2017`__

__ https://arxiv.org/pdf/1706.08500.pdf

In addition, a faster and online computation approach can be found in `Chen et al. 2014`__
In addition, a faster and online computation approach can be found in `Mathiasen et al. 2020`__

__ https://arxiv.org/pdf/2009.14075.pdf

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