> Other than a handful number of people doing some fundamental research towards understanding the theoretical concepts of these methods, almost all the community now seems to target the development of more complex pipelines (that most likely cannot be reproduced based on the elements presented in the paper) which in most of the cases have almost no theoretical reasoning behind that can add 0,1% of performance on a given benchmark. Is this the objective of academic research? Putting in place highly complex engineering models that simply explore computing power and massive annotated data?

I last dabbled in image processing research around 2011. Probably most of the papers i read during the previous 5 years were small little epsilon papers that added no real value. I did some work in other fields and noticed a similar trend there. I always attributed it to the trend of PhDs being pumped through the system in ever greater numbers and the need for researchers to publish a paper every few months.