wzzheng / TPVFormer

An academic alternative to Tesla's occupancy network for autonomous driving.
https://wzzheng.net/TPVFormer/
Apache License 2.0
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Question on hybrid ref pt 2d #24

Closed george0407 closed 1 year ago

george0407 commented 1 year ago
        ref_2d_hw = self.ref_2d_hw.clone().expand(bs, -1, -1, -1)
        hybird_ref_2d = torch.cat([ref_2d_hw, ref_2d_hw], 0)

Firstly appreciate your work, and I wonder why you concatenate the ref pts of hw for 2 layers as shown above. Thanks a lot.

huang-yh commented 1 year ago

Hi, the code is built upon BEVFormer. BEVFormer has both temporal version and spatial-only version. BEVFormer concatenates the current ref_2d and the aligned ref_2d_shift from another timestamp in its temporal version, while concatenating two same ref_2ds for the spatial-only version. Since TPVFormer does not use temporal information, we simply follow the practice of BEVFormer.

george0407 commented 1 year ago

Thanks for your answer