[D] What is the current SOTA for bootstrapping models to work on niche tasks, in vision?

It used to be that when you needed to train a model on some relatively niche classification/detection/segmentation task, you took a Resnet50 which was pretrained on ImageNet1K/COCO and finetuned it to whatever small-to-medium dataset you had, and that would be enough to jump-start your performance to something reasonable. Of course, you could always improve upon that by using a larger Resnet, improving your hyperparameter choices, or cleaning noise from your proprietary dataset.

Well, it's been years since this practice began; …

bootstrapping classification coco current dataset detection machinelearning medium resnet50 segmentation small sota tasks train vision work