Update README.md

README.md

@@ -22,6 +22,7 @@ size_categories:
 - 1K<n<10K
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 # VALERIE22 - A photorealistic, richly metadata annotated dataset of urban environments
+<img src="https://huggingface.co/datasets/Intel/VALERIE22/resolve/main/images/teaser_c.png">
 
 ## Dataset Description
 
@@ -30,9 +31,27 @@ size_categories:
 
 ### Dataset Summary
 
-The VALERIE22 dataset was generated with the VALERIE procedural tools pipeline providing a photorealistic sensor simulation rendered from automatically synthesized scenes. The dataset provides a uniquely rich set of metadata, allowing extraction of specific scene and semantic features (like pixel-accurate occlusion rates, positions in the scene and distance + angle to the camera). This enables a multitude of possible tests on the data and we hope to stimulate research on understanding performance of DNNs.
+The VALERIE22 dataset was generated with the VALERIE procedural tools pipeline (see image below) providing a photorealistic sensor simulation rendered from automatically synthesized scenes. The dataset provides a uniquely rich set of metadata, allowing extraction of specific scene and semantic features (like pixel-accurate occlusion rates, positions in the scene and distance + angle to the camera). This enables a multitude of possible tests on the data and we hope to stimulate research on understanding performance of DNNs.
 
-### Supported Tasks and Leaderboards
+<img src="https://huggingface.co/datasets/Intel/VALERIE22/resolve/main/images/VALERIE_overview1.png">
+
+Each sequence of the dataset contains for each scene two rendered images. One is rendered with the default Blender tonemapping (/png) whereas the second is renderd with our photorealistic sensor simulation (see hagn2022optimized). The image below shows the difference of the two methods.
+
+<img src="https://huggingface.co/datasets/Intel/VALERIE22/resolve/main/images/SensorSimulation.png">
+
+Following are some example images showing the unique characteristics of the different sequences.
+
+|Sequence0052|Sequence0054|Sequence0057|Sequence0058|
+|:---:|:---:|:---:|:---:|
+|<img src="https://huggingface.co/datasets/Intel/VALERIE22/resolve/main/images/seq52_1.jpg" width="500">|<img src="https://huggingface.co/datasets/Intel/VALERIE22/resolve/main/images/seq54_1.jpg" width="500">|<img src="https://huggingface.co/datasets/Intel/VALERIE22/resolve/main/images/seq57_1.jpg" width="500">|<img src="https://huggingface.co/datasets/Intel/VALERIE22/resolve/main/images/seq58_1.png" width="500">|
+
+|Sequence0059|Sequence0060|Sequence0062|
+|:---:|:---:|:---:|
+|<img src="https://huggingface.co/datasets/Intel/VALERIE22/resolve/main/images/seq59_1.jpg" width="500">|<img src="https://huggingface.co/datasets/Intel/VALERIE22/resolve/main/images/seq60_1.jpg" width="500">|<img src="https://huggingface.co/datasets/Intel/VALERIE22/resolve/main/images/seq62_1.jpg" width="500">|
+
+
+
+### Supported Tasks
 
 - pedestrian detection
 - 2d object-detection
@@ -84,7 +103,7 @@ Train/Validation/Test splits are provided
 
 ### Licensing Information
 
-Creative Commons Zero v1.0 Universal
+CC BY 4.0
 
 ### Citation Information
 Relevant publications: