Weakness: 1) Generally lacking a quantitative measure to evaluate the generated VCEs. Evaluation is mainly performed with visual inspection. 2) As the integration of cone projection shown to be helpful, however it is not clear why this particular projection is chosen. Are there other projections that are also helpful? Is there a theoretical proof that this cone projection resolves the noise of the gradients in non-robust classifiers?
Overall, I think the proposed technique yield better VCE and interesting for the community. I also think that the strengths outweigh the weakness. However, I would be open to hear other reviewers opinion here.
1) Generally lacking a quantitative measure to evaluate the generated VCEs. Evaluation is mainly performed with visual inspection.