The Inclusive Images Competition

Autor: Weimin Wang, Roman A. Solovyev, Igor Ivanov, Pavel Ostyakov, Sergey I. Nikolenko, D. Sculley, Yoni Halpern, Pallavi Baljekar, Miha Skalic, James Atwood, Eric Breck
Rok vydání: 2019
Předmět:
Zdroj: The NeurIPS '18 Competition ISBN: 9783030291341
DOI: 10.1007/978-3-030-29135-8_6
Popis: Popular large image classification datasets that are drawn from the web present Eurocentric and Americentric biases that negatively impact the generalizability of models trained on them Shreya Shankar et al. (No classification without representation: Assessing geodiversity issues in open data sets for the developing world. arXiv preprint arXiv:1711.08536, 2017). In order to encourage the development of modeling approaches that generalize well to images drawn from locations and cultural contexts that are unseen or poorly represented at the time of training, we organized the Inclusive Images competition in association with Kaggle and the NeurIPS 2018 Competition Track Workshop. In this chapter, we describe the motivation and design of the competition, present reports from the top three competitors, and provide high-level takeaways from the competition results.
Databáze: OpenAIRE