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PF-PASCAL

The proposed method, dubbed Dynamic Hyperpixel Flow, learns to compose hypercolumn features on the fly by selecting a small number of relevant layers from a deep convolutional neural network.

Data and Resources

Cite this as

Zakaria Laskar, Juho Kannala (2024). Dataset: PF-PASCAL. https://doi.org/10.57702/8scjwqry

DOI retrieved: December 3, 2024

Additional Info

Field Value
Created December 3, 2024
Last update December 3, 2024
Defined In https://doi.org/10.48550/arXiv.1712.06861
Citation
  • https://doi.org/10.48550/arXiv.2311.18540
  • https://doi.org/10.48550/arXiv.2311.04336
  • https://doi.org/10.48550/arXiv.1901.08339
  • https://doi.org/10.48550/arXiv.1901.08341
  • https://doi.org/10.48550/arXiv.2007.10587
Author Zakaria Laskar
More Authors
Juho Kannala
Homepage https://www.aalto.fi/en/research-group/visual-computer-vision/datasets/pf-pascal