Science Score: 54.0%

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  • CITATION.cff file
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  • codemeta.json file
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    Links to: arxiv.org
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    Low similarity (5.9%) to scientific vocabulary
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Repository

Basic Info
  • Host: GitHub
  • Owner: javirk
  • Language: Python
  • Default Branch: master
  • Size: 18.6 KB
Statistics
  • Stars: 5
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 3 years ago · Last pushed over 2 years ago
Metadata Files
Readme Citation

README.md

Full or Weak annotations?

This is the repository for the paper "Full or Weak annotations? An adaptive strategy for budget-constrained annotation campaigns", presented at CVPR2023. It contains the code to reproduce the experiments presented in the paper.

Links

How to run

First of all, you need a surface of a dataset. A sample surface has been stored in surfaces/sample_surface.txt. The format is:

run_name, classification share (%), segmentation share (%), IoU, Dice

Then, you will have to create a gp_config file. You can use any gp_config file in the gp_configs folder as a template. Remember to change surface_file parameter to the filename of your surface file.

Finally, you can run the method with the file gp.pyas follows:

python gp.py --config gp_configs/gp_config.txt

If you use this code or the paper, consider citing:

@inproceedings{tejero2023full,
  title={Full or Weak annotations? An adaptive strategy for budget-constrained annotation campaigns},
  author={Tejero, Javier Gamazo and Zinkernagel, Martin S and Wolf, Sebastian and Sznitman, Raphael and Neila, Pablo M{\'a}rquez},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2023}
}

Owner

  • Name: Javier Gamazo
  • Login: javirk
  • Kind: user
  • Location: Bern

AI researcher curious about too many subjects.

Citation (CITATION.cff)

cff-version: 1.2.0
title: Full or Weak Annotations?
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Javier
    family-names: Gamazo Tejero
    affiliation: 'University of Bern, Switzerland'
  - given-names: Martin S.
    family-names: Zinkernagel
    affiliation: 'Inselspital Bern, Switzerland'
  - given-names: Sebastian
    family-names: Wolf
    affiliation: 'Inselspital Bern, Switzerland'
  - given-names: Raphael
    family-names: Sznitman
    affiliation: 'University of Bern, Switzerland'
  - given-names: Pablo
    family-names: Márquez Neila
    affiliation: 'University of Bern, Switzerland'
identifiers:
  - type: url
    value: 'https://github.com/javirk/FullWeakAnnotations'
    description: Source Code
repository-code: 'https://github.com/javirk/FullWeakAnnotations'
url: 'https://javiergamazo.com/full_weak/'
date-released: 2023-06-20

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