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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

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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/