Add tracking eval server link, adjust challenge deadline (#262)

* Add tracking eval server link, adjust challenge deadline

* Replace tracking challenge logo

* Adjust deadline

python-sdk/nuscenes/eval/detection/README.md

@@ -1,5 +1,6 @@
 # nuScenes detection task
 In this document we present the rules, result format, classes, evaluation metrics and challenge tracks of the nuScenes detection task.
+Click [here](http://evalai.cloudcv.org/web/challenges/challenge-page/356) for the **EvalAI detection evaluation server**.
 ![nuScenes Singapore Example](https://www.nuscenes.org/public/images/tasks.png)
 
 ## Overview

python-sdk/nuscenes/eval/tracking/README.md

@@ -1,7 +1,7 @@
 # nuScenes tracking task
 In this document we present the rules, result format, classes, evaluation metrics and challenge tracks of the nuScenes tracking task.
-
-*Note: This page is work in progress and therefore subject to change.*
+Click [here](http://evalai.cloudcv.org/web/challenges/challenge-page/475) for the **EvalAI tracking evaluation server**. 
+![nuScenes Tracking logo](https://www.nuscenes.org/public/images/tracking_challenge.png)
 
 ## Overview
 - [Introduction](#introduction)
@@ -38,12 +38,10 @@ To evaluate the tracking results, use `evaluate.py` in the [eval folder](https:/
 In `loaders.py` we provide some methods to organize the raw box data into tracks that may be helpful.
 
 ## Participation
-*Note: The tracking server will open soon.*
-
 The nuScenes tracking evaluation server is open all year round for submission.
-To participate in the challenge, please create an account at EvalAI.
+To participate in the challenge, please create an account at [EvalAI](http://evalai.cloudcv.org/web/challenges/challenge-page/475).
 Then upload your zipped result file including all of the required [meta data](#results-format).
-The results will be exported to the nuScenes leaderboard.
+The results will be exported to the nuScenes leaderboard shown above (coming soon).
 This is the only way to benchmark your method against the test dataset.
 
 ## Challenges
@@ -54,7 +52,7 @@ Any user that cannot attend the workshop (direct or via a representative) will b
 
 ### AI Driving Olympics (AIDO), NIPS 2019
 The first nuScenes tracking challenge will be held at NIPS 2019.
-Submission will open October 1 and close December 2.
+Submission will open October 1 and close December 9.
 The leaderboard will remain private until the end of the challenge.
 Results and winners will be announced at the [AI Driving Olympics](http://www.driving-olympics.ai/) Workshop (AIDO) at NIPS 2019.
 
@@ -333,4 +331,4 @@ Users that fail to adequately report this information may be excluded from the c
 - \[5\] *"PointPillars: Fast Encoders for Object Detection from Point Clouds"*, A. H. Lang, S. Vora, H. Caesar, L. Zhou, J. Yang and O. Beijbom, In CVPR 2019.
 - \[6\] *"Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection"*, B. Zhu, Z. Jiang, X. Zhou, Z. Li, G. Yu, In arXiv 2019.
 - \[7\] *"Disentangling Monocular 3D Object Detection"*, A. Simonelli, S. R. Bulo, L. Porzi, M. Lopez-Antequera, P. Kontschieder, In arXiv 2019.
-- \[8\] *"PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud"*, S. Shi, X. Wang, H. Li, In CVPR 2019.
+- \[8\] *"PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud"*, S. Shi, X. Wang, H. Li, In CVPR 2019.