move jsonl

README.md

@@ -1,4 +1,11 @@
 ---
+license: mit
+task_categories:
+- object-detection
+tags:
+- disability-parking
+- accessibility
+- streetscape
 dataset_info:
   features:
   - name: image
@@ -34,7 +41,10 @@ task_categories:
 - object-detection
 ---
 
-# my-object-detection-dataset
+# AccessParkCV
+
+<strong>AccessParkCV</strong> is a deep learning pipeline that detects and characterizes the width of disability parking spaces from orthorectified aerial imagery. We publish a dataset of 7,069 labeled parking spaces (and 4,693 labeled access aisles), which we used to train the models making AccessParkCV possible.
+
 
 ## Dataset Description
 
@@ -90,6 +100,21 @@ categories = item["objects"]["category"]
 segmentations = item["objects"]["segmentation"]  # Polygon coordinates
 ```
 
-## License
-
-Please specify the license for this dataset.
+## Citation
+
+```bibtex
+@inproceedings{hwang_wherecanIpark,
+  title={Where Can I Park? Understanding Human Perspectives and Scalably Detecting Disability Parking from Aerial Imagery},
+  author={Hwang, Jared and Li, Chu and Kang, Hanbyul and Hosseini, Maryam and Froehlich, Jon E.},
+  booktitle={The 27th International ACM SIGACCESS Conference on Computers and Accessibility},
+  series={ASSETS '25},
+  pages={20 pages},
+  year={2025},
+  month={October},
+  address={Denver, CO, USA},
+  publisher={ACM},
+  location={New York, NY, USA},
+  doi={10.1145/3663547.3746377},
+  url={https://doi.org/10.1145/3663547.3746377}
+}
+```

dataset_info.json

@@ -1,5 +1,5 @@
 {
-  "dataset_name": "my-object-detection-dataset",
+  "dataset_name": "AccessParkCV",
   "description": "Object detection dataset with 8 classes",
   "citation": "",
   "homepage": "",