PASCAL-Part Dataset
UCLA CCVL

trainval.tar.gz80.87MB
Type: Dataset
Tags: PASCAL

Bibtex:
@article{,
title= {PASCAL-Part Dataset},
journal= {},
author= {UCLA CCVL},
year= {},
url= {},
abstract= {This dataset is a set of additional annotations for PASCAL VOC 2010. It goes beyond the original PASCAL object detection task by providing segmentation masks for each body part of the object. For categories that do not have a consistent set of parts (e.g., boat), we provide the silhouette annotation.

Statistics
Since the dataset is an annotation of the PASCAL VOC 2010, it has the same statistics as those of the original dataset. Training and validation contains 10,103 images while testing contains 9,637 images.

Usage Considerations
We provide segmentation masks for detailed body parts. One can merge several parts to get appropriate object part granularity for different tasks. For instance, "eyes", "ears", "nose", etc. can be merged into a single "head" part.

Citation
Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts
Xianjie Chen, Roozbeh Mottaghi, Xiaobai Liu, Sanja Fidler, Raquel Urtasun, Alan Yuille
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014

Acknowledgements
We thank Viet Nguyen for coordinating and leading the efforts for cleaning up the annotations. We would like to acknowledge the support by grants ARO 62250-CS and N00014-12-1-0883.
},
keywords= {PASCAL},
terms= {}
}

10 day statistics (2 downloads)

Average Time 8 mins, 32 secs
Average Speed 157.80kB/s
Best Time 1 mins, 23 secs
Best Speed 974.37kB/s
Worst Time 15 mins, 42 secs
Worst Speed 85.85kB/s
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