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diviswen / PMP-Net

MIT License
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PCN inference and test #9

Open stefano-mazz opened 2 years ago

stefano-mazz commented 2 years ago

Hi, i do not understand how is generated a 16384 point cloud in output during the inference. The input point cloud is repeated 8 times and then fed into the network as [8, 2048,3] and then obtaining 8 different outputs they are reshaped to obtain a 16384 point cloud, if i have understood correctly. By running the line partial = random_subsample(partial.repeat((1, 8, 1)).reshape(-1, 16384, 3)) i get a partial point cloud of size [1,2048,3] instead of [b*8, 2048,3]. So, the output of the network is still 2048. Can you give me further explanation about this? Thank you in advance.

AllenXiangX commented 2 years ago

@stefano-mazz The shape of the input point cloud is [b, 16384, 3], so after "partial.repeat((1, 8, 1)).reshape(-1, 16384, 3))", the shape is [b8, 16384, 3], and after the random_subsample, if becomes [b8, 2048, 3].