Update README.md

README.md

@@ -26,33 +26,172 @@ configs:
     path:
     - scene_03_04/raw/gt_pairs.csv
 ---
-### Cross-View Urban Traffic Dataset - Subset
+# Cross-View Urban Traffic Subset Dataset
+
+This repository provides a **representative sample** of the **Cross-View Urban Traffic Dataset (CVUTD)** for reviewer inspection and qualitative verification.
+
+The subset is intended to let reviewers:
+- inspect the raw and annotated data format,
+- verify annotation quality,
+- understand the cross-view correspondence structure,
+- and assess the benchmark design without downloading the full dataset.
+
+The **full dataset** is hosted separately and is available at submission time:
+- **Full dataset:** https://huggingface.co/datasets/prakharbh/CrossViewUrbanTrafficDataset
+
+---
 
 ## Dataset Summary
-The Cross-View Urban Traffic Dataset (CVUTD) is a benchmark for cross-view urban traffic perception built from synchronized ego-centric bicycle videos and aerial drone videos recorded at real urban intersections in Regensburg, Germany.
 
-The dataset is designed to support two linked tasks:
+The Cross-View Urban Traffic Dataset is a benchmark for **cross-view urban traffic perception** built from synchronized:
+- **ego-centric bicycle-mounted videos**, and
+- **aerial drone videos**
+
+recorded over real urban intersections.
+
+The benchmark supports two linked tasks:
+1. **Cross-view identity matching** between street-view and drone-view object tracks
+2. **Ego-to-BEV prediction** using aerial supervision
+
+This subset repository contains a **small but representative sample scene** from the full dataset.
+
+---
+
+## What This Subset Contains
+
+This subset contains one representative scene with synchronized cross-view traffic data and benchmark annotations.
+
+Typical files included are:
+- `street.mp4` or `street_annotated.mp4`
+- `drone.mp4` or `drone_annotated.mp4`
+- `street_annotations.csv`
+- `drone_annotations.csv`
+- `gt_pairs.csv`
+
+Depending on the uploaded version, additional processed files may also be present:
+- `frame_matches.csv`
+- `track_mapping.csv`
+- `coord_align.csv`
+
+These files are sufficient for reviewers to inspect:
+- scene structure,
+- tracked detections in both views,
+- manually verified cross-view ground-truth correspondences,
+- and the benchmark’s tabular annotation format.
+
+---
+
+## How This Sample Was Created
+
+This subset was created by selecting **one complete scene** from the full benchmark release and publishing its associated benchmark files as a lightweight, reviewable sample.
+
+The sample was chosen to be **representative** of the full dataset in the following ways:
+- it contains synchronized **ego-view and drone-view** observations of the same urban intersection scene,
+- it includes tracked traffic participants in both views,
+- it contains manually verified **cross-view identity correspondences** in `gt_pairs.csv`,
+- and it reflects the same annotation and preprocessing format used throughout the full dataset.
+
+This subset is **not a different dataset** and does not use a different processing pipeline. It is simply a reduced release of the same benchmark format used in the full dataset.
+
+---
+
+## File Format Description
+
+### `street_annotations.csv`
+Street-view tracked detections, typically including:
+- frame index
+- track ID
+- class label
+- bounding box coordinates
 
-Cross-view identity matching between street-view and drone-view object tracks
+### `drone_annotations.csv`
+Drone-view tracked detections, typically including:
+- frame index
+- track ID
+- class label
+- bounding box coordinates
+- metric world coordinates (when available)
 
-Ego-to-BEV prediction using aerial supervision
+### `gt_pairs.csv`
+Human-verified cross-view ground-truth correspondences:
+- `scene_id`
+- `street_track_id`
+- `drone_track_id`
+- `class_name`
 
-The benchmark focuses on intersection-centric traffic analysis, where local interactions, identity preservation, and global spatial structure must be reasoned about jointly across views.
+This file defines the benchmark identity supervision linking street-view and drone-view tracks.
 
-## Dataset Structure
+---
+
+## Intended Purpose of the Subset
+
+This subset is provided to support:
+- reviewer inspection,
+- format verification,
+- benchmark transparency,
+- and lightweight qualitative inspection of the released data.
+
+It is **not intended** to replace the full dataset for training or large-scale benchmarking.
+
+For full experiments, use the complete dataset release:
+- https://huggingface.co/datasets/prakharbh/CrossViewUrbanTrafficDataset
+
+---
 
-A typical scene contains:
+## Relationship to the Full Dataset
 
-- synchronized street-view video
+This repository is a **subset release** of the full Cross-View Urban Traffic Dataset.
 
-- synchronized drone-view video
+The full dataset contains:
+- multiple urban intersections,
+- substantially more tracked traffic participants,
+- more cross-view correspondences,
+- and the full benchmark scope used in the paper.
 
-- street-view detection/tracking CSV
+This subset exists only to provide a compact and accessible sample for inspection and review.
 
-- drone-view detection/tracking CSV
+---
+
+## Privacy and Anonymization
+
+The data were recorded in real urban traffic environments. To support responsible release:
+- human faces are anonymized,
+- vehicle license plates are anonymized,
+- and the subset is intended only for research and benchmark inspection.
+
+The dataset is **not intended** for surveillance, face recognition, license-plate recognition, or person re-identification.
+
+---
+
+## License
+
+This subset is released under the same license as the full dataset:
+
+**CC-BY-NC-ND 4.0**
+
+Please refer to the full dataset page for release details and usage conditions.
+
+---
+
+## Code and Benchmark Pipeline
+
+Code, preprocessing scripts, annotation tools, baseline implementations, and evaluation scripts are available at:
+
+- **GitHub repository:** https://github.com/oth-aifiud/Cross-View-Urban-Traffic-Dataset
+
+For whole-dataset processing and evaluation across multiple scenes, use the batch scripts in the `batch_scripts/` directory of the code repository.
+
+---
 
-- verified cross-view correspondences
+## Citation
 
-- processed wedge-filtered matching artifacts
+If you use this dataset or subset in research, please cite the associated paper and dataset release.
 
-- alignment metadata for BEV evaluation
+```bibtex
+@misc{crossviewurbantrafficdataset,
+  title={Cross-View Urban Traffic Dataset},
+  author={Prakhar Bhardwaj and collaborators},
+  year={2026},
+  howpublished={Hugging Face dataset repository},
+  url={https://huggingface.co/datasets/prakharbh/CrossViewUrbanTrafficDataset}
+}