prakharbh/CrossViewUrbanTrafficSubsetDataset

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

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Dataset Summary

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.

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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.

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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.

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File Format Description

street_annotations.csv

Street-view tracked detections, typically including:

• frame index
• track ID
• class label
• bounding box coordinates

drone_annotations.csv

Drone-view tracked detections, typically including:

• frame index
• track ID
• class label
• bounding box coordinates
• metric world coordinates (when available)

gt_pairs.csv

Human-verified cross-view ground-truth correspondences:

• scene_id
• street_track_id
• drone_track_id
• class_name

This file defines the benchmark identity supervision linking street-view and drone-view tracks.

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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

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Relationship to the Full Dataset

This repository is a subset release of the full Cross-View Urban Traffic Dataset.

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.

This subset exists only to provide a compact and accessible sample for inspection and review.

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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.

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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.

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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.

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Citation

If you use this dataset or subset in research, please cite the associated paper and dataset release.

@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}
}