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Hi, point net was originally trained on a fixed-sized input , and I wonder if there is a efficient way to deal with different numbers of points in a batch. for example, (3, 10) and (3, 11) are my samples, how I should use them in the same batch ??? is there any better way than padding & passing mask that it'd used in NLP ???
The text was updated successfully, but these errors were encountered:
Hi, point net was originally trained on a fixed-sized input , and I wonder if there is a efficient way to deal with different numbers of points in a batch. for example, (3, 10) and (3, 11) are my samples, how I should use them in the same batch ??? is there any better way than padding & passing mask that it'd used in NLP ???
The text was updated successfully, but these errors were encountered: