Inclusive Images Challenge

Deadline: 2018-11-05
Award: $25,000
Open to: 18 Years and Older*

Some open source data sets have been found to be geographically skewed based on how they were collected. Because the shape of a dataset informs what an ML model learns, such skew may cause the research community to inadvertently develop models that may perform less well on images drawn from geographical regions under-represented in those data sets.

While Google is focusing on building even more representative datasets, we also want to encourage additional research in the field around ways that machine learning methods can be more robust and inclusive when learning from imperfect data sources.

This competition challenges you to use Open Images, a large, multilabel, publicly-available image classification dataset that is majority-sampled from North America and Europe, to train a model that will be evaluated on images collected from a different set of geographic regions across the globe.