Weaknesses: 1. Novelty - The contributions of the paper in terms of novelty are: (i) The idea of using OT based distribution matching loss, (ii) theoretical results showing that such loss results in lower error, (iii) empirical results showing that such a loss indeed results in lower error. For the crowd counting community, this may be considered as considerable contributions. However, the paper does not address if this is of interest to the broader vision/ml community - which is expected for a Neurips kind of venue. For example, the authors could have considered a broader set of applications like object detection for evaluating their method. Further, the authors should have given a better background for the recent works that have focussed on improving representation of ground-truth [2,9,10] for training the networks.

I was wondering if anyone else have similar feelings with regards to a number of accepted papers coming from Chinese universities/authors presented in ICCV. Thus far in the conference, I came across quite a lot of papers with questionable motives which made me question the ethical consequences. These papers are, for the most part, concerned with various forms of person identification (i.e., typical big brother stuff). In fact, when you look at the accepted papers, more than 80% of any kind of identification papers have Chinese authors/affiliations. But that's not all, some papers go to extreme lengths of person re-identification such as: And maybe you think person re-identification is all there is, but its not.