Interactive Labeling and Data Augmentation for Vision

ICCV 2021 Workshop

About

The workshop on Interactive Labeling and Data Augmentation for Vision (ILDAV) wishes to address novel ways to solve computer vision problems where large quantities of labeled image data may not be readily available. It is important that datasets of sufficient size can be quickly and cheaply acquired and labeled. More specifically, we are interested in solutions to this problem that make use of (i) few-click and interactive data annotation, where machine learning is used to enhance human annotation skill, (ii) synthetic data generation, where one uses artificially generated data to augment real datasets, and (iii) weak supervision, where auxiliary or weak signals are used instead of (or to complement) manual labels.

More broadly, we aim at fostering a collaboration between academia and industry in terms of leveraging machine learning research and human-in-the-loop, interactive labeling to quickly build datasets that will enable the use of powerful deep models in all problems of computer vision.

The workshop topics include (but are not limited to):

The workshop will be held at ICCV 2021, which will follow a virtual format, on October 11 (afternoon).

Invited Speakers

Angela
Dai
TU Munich
Gim Hee
Lee
National University of Singapore
Vittorio
Ferrari
Google, University of Edinburgh

Call for Papers

We invite authors to submit unpublished papers that follow the theme and topics of our workshop. Accepted papers will be presented at a poster session. All submissions will go through a double-blind review process. Papers will be selected based on relevance, significance and novelty of results, technical merit, and clarity of presentation.

Submitted papers shall be:

  • Full-length papers (up to 8 pages + references), or
  • Extended abstracts (4 pages, incl. references) presenting early results inviting further research.

  • Accepted full-length papers will be published in the ICCV 2021 proceedings.

    Work that has previously been presented at a non-archival venue is acceptable. For extended abstracts, we accept (and encourage) work-in-progress, or negative/partial results.

    Submissions should be made through the CMT website: https://cmt3.research.microsoft.com/ILDAV2021.

    Papers should be formatted according to the ICCV guidelines: http://iccv2021.thecvf.com/node/4#submission-guidelines.

    Awards

    We will be giving out Best Paper and Best Paper (Runner Up) awards at the workshop. The awards will be sponsored by Sama.

    Important dates

    All deadlines are set to 23h59 Pacific Daylight Time (PDT, UTC-7).

    News

    Organizers

    Frédéric
    Ratle
    Sama
    Martine
    Bertrand
    Sama
    Loic
    Juillard
    Sama
    Sasha
    Luccioni
    Mila and University of Montreal
    Christian
    Gagné
    Université Laval
    Jean-François
    Lalonde
    Université Laval

    Contact

    Please reach us with any questions at ildav-workshop at sama.com.

    Thank you to the Image Matching Workshop for the template

    Sponsors