Start: Feb. 23, 2022, midnight
Description: in this stage, participants are asked to develop a model to perform semantic segmentation of RGB images, that is, to distinguish crop, weed, and background pixels. Participants receive the Training_Dev_2019 set with 448 labeled images and are asked to submit predictions of the unlabelled Test_Dev_2019 set containing 52 images. At the end of the Development stage, the labels of the Test_Dev_2019 set are released. During this stage, participants will also receive 16 images that are part of the Test_Gen_2021 set to prepare for the next stage.
Start: April 6, 2022, noon
Description: in this stage, participants are asked to submit predictions of the new unlabelled Test_Gen_2021 set (246 images) by using their models trained on the 2019 dataset composed of 500 images. The Test_Gen_2021 set has been collected by the same sensors and in the same field of the 2019 dataset. However, different environmental conditions and sensors’ settings require the models to have generalization capability. The generalization capability can be reached by applying for style transfer and/or domain adaptation techniques.
Start: May 17, 2022, noon
Description: in this stage, participants are required to submit predictions of the new unlabelled Test_Final_2021 set containing 252 images. This stage is thought to submit the final model without major changes; thus, the duration is limited to three days and the number of submissions to three.
May 21, 2022, noon
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