Name | DL | Torrents | Total Size | Deep Learning [edit] | 50 | 963.86GB | 462 | 0 | Computer Vision [edit] | 79 | 1.41TB | 619 | 0 | PASCAL Visual Object Classes Challenge [edit] | 12 | 13.73GB | 88 | 0 |
trainval.tar.gz | 80.87MB |
Type: Dataset
Tags: PASCAL
Bibtex:
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= {} }