This is becoming incredibly common in Machine Learning and Computer Vision. Too many papers, too much interest in the area, not enough good reviewers, and no good second-tier or third-tier conferences that would act as a relief valve. The result is that the same potentially poor papers are getting resubmitted verbatim over and over again, potentially many times, in the hopes that they will eventually be stochastically accepted.
See the 2014 NeurIPS experiment, where the program committee sent some of their submitted papers through two separate reviews. The goal was to find out whether the accept/reject recommendations would be consistent. The greatly simplified explanation of their result is that really good papers will always be accepted, and really bad papers will always be rejected, but for the large bulk of the papers of middle quality that are rejected, there's a good chance your paper will be accepted if you just resubmit verbatim next time. Many authors have interpreted this as meaning that a rejected paper has about a 25% chance of being accepted if you just resubmit next time.
This is a problem that AI/ML/CV is dealing with right now. There's not much you can do about it. If the paper is unchanged, then copy/paste your review from last time and move on.