>company

Looking forward to hearing what you think. Just to be clear. I'm always reluctant to calling one dataset better than another because it always depends on what you're trying to achieve with it. With Sama-Coco, we were trying to fix some of the misclassification errors when possible but we also put a significant amount of effort in drawing precise polygons around the objects of interest because of experiments we are currently running. And, of course, we wanted to capture as many instances of the COCO classes as possible. This resulted in a dataset with close to 25% more object instances than the original COCO 2017 dataset. But it's not to say that we solved all "errors" in COCO. :)