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.

Data and Resources

Cite this as

R. Mottaghi, X. Chen, X. Liu, N. Cho, S. Lee, S. Fidler, R. Urtasun, A. Yuille (2024). Dataset: PASCAL Context. https://doi.org/10.57702/i5758bop

DOI retrieved: December 2, 2024

Additional Info

Field Value
Created December 2, 2024
Last update December 2, 2024
Defined In https://doi.org/10.48550/arXiv.2003.10211
Citation
  • https://doi.org/10.48550/arXiv.2304.06957
  • https://doi.org/10.48550/arXiv.1911.07257
  • https://doi.org/10.48550/arXiv.2312.13514
  • https://doi.org/10.48550/arXiv.2108.06536
  • https://doi.org/10.48550/arXiv.2002.07371
  • https://doi.org/10.48550/arXiv.1701.07122
Author R. Mottaghi
More Authors
X. Chen
X. Liu
N. Cho
S. Lee
S. Fidler
R. Urtasun
A. Yuille
Homepage https://www.pascal-voc.org/