First Workshop on Interactive Labeling and Data Augmentation for Vision

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):

Interactive and Few-click annotation
Data augmentation
Synthetic data for training models
Weak supervision
Human-in-the-loop learning

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We invite authors to submit unpublished papers that follow the theme and topics of our workshop.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 monetary prizes to the best papers:

Best Paper: $500

Best Paper (Runner Up): $300

The awards are sponsored by Sama.

The 2021 Awards were given to the following papers:

Best Paper: Gyungin Shin, Weidi Xie, Samuel Albanie. All you need are a few pixels: semantic segmentation with PixelPick.

Best Paper (Runner Up): Robby Neven et al. Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty.

Congratulations to the winners!

Important dates

Paper submission deadline: ~~July 27, 2021~~ July 30, 2021.
Notification to authors: August 10, 2021.
Camera-ready deadline: August 17, 2021.
Workshop date: October 11, 2021 (afternoon).

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

News

October 15: Recordings and posters are now available in the Program section. Thanks for attending!
September 27: Program available.
June 1: Call for papers ready.
April 26: New website.