NeurIPS 2020

Learning Semantic-aware Normalization for Generative Adversarial Networks

Meta Review

R3 and R4 rate the paper top 50% papers, while R1 votes the paper marginally below the bar. While R1 initially raised several concerns on the paper's novelty side, R1 upgrades the rating of the paper since the rebuttal addresses the concerns. After consolidating the reviews and rebuttal, the AC finds the proposed method interesting. The channel grouping and normalization based on the filter similarity is new for generator design, and the results and analysis presented in the paper support the claim. The AC determines that the paper has merits to be published in the NeurIPS conference and would like to recommend its acceptance.