Venue: ICLR 2023 TinyPapers

Reviews:

final_score: rating: Clear, Correct, and Reproducible (CCR): a submission which meets the reviewing criteria
review_content: summary_of_contributions: This tiny paper provides a method for utilizing GradCam for 3D Point Cloud Semantic Segmentation architecture 
strengths_and_weaknesses: ### Strengths:
- The paper is clear, well-motivated and proposes a solution to an important problem.

### Weaknesses:
1. The paper should mention the performance of the RandLA-Net semantic segmentation architecture. I want to see whether the GradCam performance in 3D point clouds affected by the underlying semantic segmentation module.


suggested_changes: Overall, I find this submission to be Clear, Correct and Reproducible. I also have some clarifications regarding the approach, stated below:
1. Why is Truck class harder and more prone to errors than any other class? Is it because the underlying segmentation module also had a low IoU segmentation performance for this class?
2. The authors mentioned "higher derivatives lead to better localization and smoother heatmaps at last decoder layers". Did the authors verify this using qualitative plots as well? Or was this claim made on just the quantitative performance reported in Table 1?
review_title: null

final_score: rating: Clear, Correct, and Reproducible (CCR): a submission which meets the reviewing criteria
review_content: summary_of_contributions: Reviews for Paper #86
strengths_and_weaknesses: This paper proposes a gradient analysis technique on models for point cloud semantic segmentation.

1. Clear formulations of the gradient importance and heatmaps are given and easy to follow;
2, FIgures provide intuitive demonstrations; 
3, The technical novelty seems to be limited for mainstream venues. However, I think this paper meets the criteria in terms of clarify, correctness, and reproducibility. Thus, I vote for acceptance.  
 

suggested_changes: 1, Examination of the proposed methods on more segmentation models are encouraged.
review_title: null

Decision: Invite to present