15+

Real-world large-scale Scenes

798,000,000+

Pixels Per Frame

104,196+

Head points

102,184,000+

Bounding Boxes

PANDA Dataset Introduction

PANDA is the first gigaPixel-level humAN-centric viDeo dAtaset, for large-scale, long-term, and multi-object visual analysis. The videos in PANDA were captured by a gigapixel camera and cover real-world large-scale scenes with both wide field-of-view (~1km^2 area) and high resolution details (~gigapixel-level/frame). The scenes may contain 4k head counts with over 100× scale variation. PANDA provides enriched and hierarchical ground-truth annotations, including 10,218.4k bounding boxes, 111.8k fine-grained attribute labels, 8.4k trajectories, 1.5k groups and 2.9k interactions.

If you use our dataset, please cite the following paper:

Multiscale gigapixel video: A cross resolution image matching and warping approach

@inproceedings{yuan2017multiscale,
title={Multiscale gigapixel video: A cross resolution image matching and warping approach},
author={Yuan, Xiaoyun and Fang, Lu and Dai, Qionghai and Brady, David J and Liu, Yebin},
booktitle={Computational Photography (ICCP), 2017 IEEE International Conference on},
pages={1--9},
year={2017},
organization={IEEE}
}

Professors in Our Team

Lu Fang

Tsinghua University

Shengjin Wang

Tsinghua University

Qionghai Dai

Tsinghua University

David J. Brady

Duke University
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