> I guess I'm just asking if COCO or ImageNet-trained networks are actually noticeably superior for most real-world tasks, or if it's just a metric that's used because the performance differences only show up in the long tail of the distribution.
Given that for any real-world vision task you start from a pretrained model om those datasets they will in fact be noticably superior on the real world task after finetuning. Just because the quality of the features extracted through the backbone is better.
Given that for any real-world vision task you start from a pretrained model om those datasets they will in fact be noticably superior on the real world task after finetuning. Just because the quality of the features extracted through the backbone is better.