Update README.md

README.md

@@ -1,12 +1,13 @@
-# Waymo motion prediction challenge 2022: 3rd place solution
+# Waymo motion prediction challenge 2022: 3rd place solution (May, 26)
 ## Our implementation of [MultiPath++](https://arxiv.org/abs/2111.14973)
 
 ![](docs/architecture.png)
 
 
 ## General Info:
-- 📜[**Technical report**](docs/WMPC_Report_2022.pdf)   
-- 🥉[Waymo Motion Prediction Challenge Website](https://waymo.com/open/challenges/2022/motion-prediction/)
+- 🏎️[**CVPR2022 Workshop on Autonomous Driving website**](https://cvpr2022.wad.vision)
+- 📜[**Technical report**](https://arxiv.org/abs/2206.10041)   
+- 🥉[**Waymo Motion Prediction Challenge Website**](https://waymo.com/open/challenges/2022/motion-prediction/)
 
 ## Team behind this solution:
 Stepan Konev 
@@ -32,4 +33,20 @@ Once we have our data prepared we can run the training.
 python3 train.py configs/final_RoP_Cov_Single.yaml
 ```
 
-If you find this work interesting please ⭐️star and share this repo.
+If you find this work interesting please ⭐️star and share this repo.
+
+## Citation
+If you find this work useful please cite us
+```
+@misc{https://doi.org/10.48550/arxiv.2206.10041,
+  doi = {10.48550/ARXIV.2206.10041},
+  url = {https://arxiv.org/abs/2206.10041},
+  author = {Konev, Stepan},
+  keywords = {Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  title = {MPA: MultiPath++ Based Architecture for Motion Prediction},
+  publisher = {arXiv},
+  year = {2022},
+  copyright = {arXiv.org perpetual, non-exclusive license}
+}
+
+```