NeurIPS 2020

Consistent Structural Relation Learning for Zero-Shot Segmentation

Meta Review

Paper originally received a set of somewhat mixed reviews from four reviewers, with scores: 8, 5, 5, 6. Generally, the reviewers liked the work, commenting on how it addressed an important problem [R3] and presented a well-motivated idea [R1] that was novel [R2], simple and reproducible [R1]; ultimately resulting in good results [R1,R2,R3,R4]. Some shortcoming were also identified, including (1) unclear positioning and potential limited novelty with respect to [1] [R1,R2,R3] and (2) lack of sufficient comparisons to related work [R2,R3,R4]. Authors have provided a very through rebuttal that addressed all major concerns; providing compelling clarification of novelty (1) and additional experiments to address reviews comments for (2). As a result R2 and R3 raised their scores arriving at the final unanimously positive ratings for the paper of: 8, 7, 6, 6. AC has read the reviews, the rebuttal, resulting discussion and the paper itself. AC agrees with reviewers that the paper proposes an interesting solution for a challenging problem, with significant improvements over SoTA. Based on the consensus of reviewers and the AC, the decision is to Accept the paper.