Samuel Albanie
Description: Interactive Labeling and Data Augmentation for Vision - ICCV 2021 Workshop
workshop (5272) labeling (183) annotation (89) synthetic data (16) data augmentation (9) iccv (8) iccv 2021 (1)
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, (i
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):
Samuel Albanie