The only shortcut I can give you is to look on Kaggle to see what the competitors have used. Most of the papers are not suitable for real world applications. It's not really about the complexity or scale of the task, but rather that the authors leave out some important information. For example, in object detection, there is DETR, but if you look on Kaggle, nobody uses that. The reason is that the original DETR has too slow a convergence speed and was only trained on 640 size images. Instead, many people still use YOLO. But you don't realize that until you try it yourself or someone tells you.