PASCAL Context

doi:doi:10.57702/i5758bop

PASCAL Context

The PASCAL Context dataset is a benchmark for multi-task learning in computer vision. It contains 10103 images with 5 tasks: semantic segmentation, human body part segmentation, surface normal estimation, saliency estimation, and edge detection.

BibTex:

@dataset{R_Mottaghi_and_X_Chen_and_X_Liu_and_N_Cho_and_S_Lee_and_S_Fidler_and_R_Urtasun_and_A_Yuille_2024,
    abstract = {The PASCAL Context dataset is a benchmark for multi-task learning in computer vision. It contains 10103 images with 5 tasks: semantic segmentation, human body part segmentation, surface normal estimation, saliency estimation, and edge detection.},
    author = {R. Mottaghi and X. Chen and X. Liu and N. Cho and S. Lee and S. Fidler and R. Urtasun and A. Yuille},
    doi = {10.57702/i5758bop},
    institution = {No Organization},
    keyword = {'Edge Detection', 'Human Body Part Segmentation', 'Image Segmentation', 'Object Detection', 'PASCAL Context', 'Saliency Estimation', 'Segmentation', 'Semantic Segmentation', 'Surface Normal Estimation', 'image segmentation', 'object detection', 'pascal context', 'semantic segmentation'},
    month = {dec},
    publisher = {TIB},
    title = {PASCAL Context},
    url = {https://service.tib.eu/ldmservice/dataset/pascal-context},
    year = {2024}
}