tusen-ai / SST

Code for a series of work in LiDAR perception, including SST (CVPR 22), FSD (NeurIPS 22), FSD++ (TPAMI 23), FSDv2, and CTRL (ICCV 23, oral).
Apache License 2.0
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Directly inference with my own dataset for CTRL #144

Closed Eddiesyn closed 1 year ago

Eddiesyn commented 1 year ago

I would like to directly inference the pretrained model of CTRL on my own dataset. But i found that the model input point cloud has intensity and elongation as its additional feature input. I'm wondering

  1. is there a model version of not using elongation or intensity as input; or such ablation studies showing the impact of it on the final result;
  2. is there a way of hacking a dummy elongation into the input (like always use 0, or any valid constant option, since the elongation input dimension is transformed with a tanh function). Just faking that all point cloud has same elongation.
Abyssaledge commented 1 year ago

You can remove intensity and elongation, which leads to a minimal performance drop. However, you need to retrain the model. We do not have off-the-shelf pretrained models ignoring intensity and elongation.

Eddiesyn commented 1 year ago

Thanks for the quick rely!