Add call for contributions

sinanh · Jun 4, 2020 · 84513d1 · 84513d1
1 parent 5a74be9
commit 84513d1
Show file tree

Hide file tree

Showing 2 changed files with 41 additions and 7 deletions.
diff --git a/README.md b/README.md
@@ -20,20 +20,15 @@ docker build -t keras-io . && docker run --rm -p 8000:8000 keras-io
 It will take a while the first time because it's going to pull the 
 image and the dependencies, but on the next times it'll be much faster.
 
+
 ## Call for examples
 
 Are you interested in submitting new examples for publication on keras.io?
 We welcome your contributions!
 Please read the information below about adding new code examples.
 
-We are currently interested in the following examples:
+We are currently interested in [the following examples](https://github.com/keras-team/keras-io/blob/master/call_for_contributions.md).
 
-- A3C and A2C RL
-- Retinanet
-- YoloV3
-- StyleGAN
-- BERT
-- End-to-end OCR (with CTC loss)
 
 
 ## Adding a new code example

diff --git a/call_for_contributions.md b/call_for_contributions.md
@@ -0,0 +1,39 @@
+# Call for code example contributions
+
+This is a constantly-updated list of code examples that we're currently interested in.
+
+## Timeseries forecasting with LSTM for weather prediction
+
+Recommendations:
+
+- Use `timeseries_dataset_from_array` for data processing
+- Single LSTM layer + classification layer, trained with `fit()`
+- Add nice visualizations
+
+
+## StyleGAN / StyleGAN2
+
+[Reference paper 1](https://arxiv.org/abs/1812.04948) [2](https://arxiv.org/abs/1912.04958)
+[Reference TF implementation](https://github.com/NVlabs/stylegan2)
+
+
+## End-to-end OCR
+
+[Old Keras example](https://github.com/keras-team/keras/blob/master/examples/image_ocr.py)
+
+Recommendations:
+
+- Use CTC loss
+- Can use either Transformer model or recurrent model (whichever works best)
+
+
+
+## Improve next-frame prediction with ConvLSTM
+
+[Current example](https://keras.io/examples/vision/conv_lstm/)
+
+Recommendations:
+
+- Find a better, more interesting dataset
+- Make it work better
+- Add detailed explanations