r/MachineLearning - [R] Object-recognition dataset stumped the world's best computer vision models

If you break the IID assumption then models that rely on it don't perform well. Everyone knows that Imagenet is a relatively clean dataset and not representative of the real world. They didn't train on a split of objectnet and test on a split, they trained on imagenet and then just applied to the common categories. All this shows is that if the training data is not representative of the testing data, performance will suffer. This is one of the first things everyone learns in this field.