Call for participation: VISDA-2022 Domain Adaptation Challenge

[Piotr Teterwak]

We are pleased to announce the 2022 Visual Domain Adaptation (VisDA2022) Challenge! It is well known that the success of machine learning methods on visual recognition tasks is highly dependent on access to large labeled datasets. Unfortunately, performance often drops significantly when the model is presented with data from a new deployment domain which it did not see in training, a problem known as domain shift. The VisDA challenge aims to test domain adaptation methods’ ability to transfer source knowledge and adapt it to novel target domains. 

This year, we’re tackling the problem of automated waste sorting. Single-stream recycling is imperfect and many recyclables get placed in the landfill. One way to improve it is through automated sorting. We have collected real-world data from several locations and seasons, and generated synthetic data as well. We formulate this as a domain adaptation problem with synthetic + location/season 1 as the source, and location/season 2 as the target. This formulation aims to capture the real-world challenge of rapid adaptation to new locations.

$3000 in cash prizes for top 3 teams ($1000 for 1st, $500 for 2nd and 3rd), as well as an opportunity to present at our NeurIPS workshop. The competition runs through

October 10th. 

Tell your friends, and participate. More info here: https://ai.bu.edu/visda-2022/. 

Thank you,

VisDA Organizers