wzzheng / TPVFormer

[CVPR 2023] An academic alternative to Tesla's occupancy network for autonomous driving.
https://wzzheng.net/TPVFormer/
Apache License 2.0
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请问怎么理解 num_points_in_pillar=[4, 32, 32] 这个参数? #23

Closed huaifeng1993 closed 1 year ago

huaifeng1993 commented 1 year ago
 ref_3d_hw = self.get_reference_points(tpv_h, tpv_w, pc_range[5]-pc_range[2], num_points_in_pillar[0], '3d', device='cpu')#【1,4,10000,3】

        ref_3d_zh = self.get_reference_points(tpv_z, tpv_h, pc_range[3]-pc_range[0], num_points_in_pillar[1], '3d', device='cpu')
        ref_3d_zh = ref_3d_zh.permute(3, 0, 1, 2)[[2, 0, 1]]
        ref_3d_zh = ref_3d_zh.permute(1, 2, 3, 0)#【1,32,800,3】

        ref_3d_wz = self.get_reference_points(tpv_w, tpv_z, pc_range[4]-pc_range[1], num_points_in_pillar[2], '3d', device='cpu')
        ref_3d_wz = ref_3d_wz.permute(3, 0, 1, 2)[[1, 2, 0]]
        ref_3d_wz = ref_3d_wz.permute(1, 2, 3, 0)#【1,32,800,3】

最后的3表示的是xyz,但是前面的4,32,32这个维度表示的是?

huaifeng1993 commented 1 year ago

看到解释了,D: sample D points uniformly from each pillar.表示的是每条雷达线上均匀抽样的点。