Update tff_for_research.md with mention of GLDv2 and CelebA.
@@ -72,6 +72,18 @@ Datasets include:
clients. For more details, see the
[API](https://www.tensorflow.org/federated/api_docs/python/tff/simulation/datasets/cifar100/load_data).
+* [**Google Landmark v2 dataset**](https://www.tensorflow.org/federated/api_docs/python/tff/simulation/datasets/gldv2/load_data)
+ The dataset consists of photos of various world landmarks, with images
+ grouped by photographer to achieve a federated partitioning of the data. Two
+ flavors of dataset are available: a smaller dataset with 233 clients and
+ 23080 images, and a larger dataset with 1262 clients and 164172 images.
+
+* [**CelebA**](https://www.tensorflow.org/federated/api_docs/python/tff/simulation/datasets/celeba/load_data)
+ A dataset of examples (image and facial attributes) of celebrity faces. The
+ federated dataset has each celebrity's examples grouped together to form a
+ client. There are 9343 clients, each with at least 5 examples. The dataset
+ can be split into train and test groups either by clients or by examples.
+
## High performance simulations
While the wall-clock time of an FL _simulation_ is not a relevant metric for
