COCO-Stuff, Pascal-VOC, and Pascal-Context

doi:doi:10.57702/b55l74tf

COCO-Stuff, Pascal-VOC, and Pascal-Context

The dataset used in the paper is COCO-Stuff, Pascal-VOC, and Pascal-Context. COCO-Stuff is an extensive semantic segmentation dataset comprising 171 categories, encompassing 80 things classes and 91 stuff classes. It contains 117k training images and 5k validation images and it is divided into 156 seen classes and 15 unseen classes. Pascal-VOC consists of 11,185 training images and 1,449 validation images across 20 classes. PASCAL Context provides supplementary annotations for PASCAL VOC 2010, consisting of 4,998 training images and 5,005 validation images.

BibTex:

@dataset{Yunheng_Li_and_Zhong-Yu_Li_and_Quansheng_Zeng_and_Qibin_Hou_and_Ming-Ming_Cheng_2024,
    abstract = {The dataset used in the paper is COCO-Stuff, Pascal-VOC, and Pascal-Context. COCO-Stuff is an extensive semantic segmentation dataset comprising 171 categories, encompassing 80 things classes and 91 stuff classes. It contains 117k training images and 5k validation images and it is divided into 156 seen classes and 15 unseen classes. Pascal-VOC consists of 11,185 training images and 1,449 validation images across 20 classes. PASCAL Context provides supplementary annotations for PASCAL VOC 2010, consisting of 4,998 training images and 5,005 validation images.},
    author = {Yunheng Li and Zhong-Yu Li and Quansheng Zeng and Qibin Hou and Ming-Ming Cheng},
    doi = {10.57702/b55l74tf},
    institution = {No Organization},
    keyword = {'COCO-Stuff', 'Pascal-Context', 'Pascal-VOC', 'Semantic Segmentation'},
    month = {dec},
    publisher = {TIB},
    title = {COCO-Stuff, Pascal-VOC, and Pascal-Context},
    url = {https://service.tib.eu/ldmservice/dataset/coco-stuff--pascal-voc--and-pascal-context},
    year = {2024}
}