Update README.md

README.md

@@ -20,7 +20,7 @@ task_ids:
 pretty_name: PP4AV
 ---
 
-# Dataset Card for WIDER FACE
+# Dataset Card for PP4AV
 
 ## Table of Contents
 - [Table of Contents](#table-of-contents)
@@ -55,15 +55,7 @@ pretty_name: PP4AV
 
 ### Dataset Summary
 
-WIDER FACE dataset is a face detection benchmark dataset, of which images are
-selected from the publicly available WIDER dataset. We choose 32,203 images and
-label 393,703 faces with a high degree of variability in scale, pose and
-occlusion as depicted in the sample images. WIDER FACE dataset is organized
-based on 61 event classes. For each event class, we randomly select 40%/10%/50%
-data as training, validation and testing sets. We adopt the same evaluation
-metric employed in the PASCAL VOC dataset. Similar to MALF and Caltech datasets,
-we do not release bounding box ground truth for the test images. Users are
-required to submit final prediction files, which we shall proceed to evaluate.
+PP4AV is the first public dataset with faces and license plates annotated with driving scenarios. P4AV provides 3,447 annotated driving images for both faces and license plates. For normal camera data, dataset sampled images from the existing videos in which cameras were mounted in moving vehicles, running around the European cities. The images in PP4AV were sampled from 6 European cities at various times of day, including nighttime. This dataset use the fisheye images from the WoodScape dataset to select 244 images from the front, rear, left, and right cameras for fisheye camera data. PP4AV dataset can be used as a benchmark suite (evaluating dataset) for data anonymization models in autonomous driving.
 
 ### Supported Tasks and Leaderboards