Hi, I really like this paper and codes!
The codes are so clean and easy to understand :)
I have a question about ablation results regarding "Multi-view feature aggregation" (Section 3.2.1) in the paper.
The paper says that a global feature, which consists of mean/variance of multi-view features, improves the model's occlusion handling capability against a direct average or max-pooling in a PointNet.
But I cannot find experiments about this in the manuscript and suppl.
Could you give some results for the statement? Or at least some insights!
Hi, I really like this paper and codes! The codes are so clean and easy to understand :)
I have a question about ablation results regarding "Multi-view feature aggregation" (Section 3.2.1) in the paper. The paper says that a global feature, which consists of mean/variance of multi-view features, improves the model's occlusion handling capability against a direct average or max-pooling in a PointNet. But I cannot find experiments about this in the manuscript and suppl.
Could you give some results for the statement? Or at least some insights!
Many thanks in advance.