bradyz / cross_view_transformers

Cross-view Transformers for real-time Map-view Semantic Segmentation (CVPR 2022 Oral)
MIT License
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camera internal and external parameters #7

Closed duohaoxue closed 2 years ago

duohaoxue commented 2 years ago

Hello, model training must be heavily dependent on camera extrinsic and extrinsic parameters? Will the effect be much worse if I use it?

  I_inv = batch['intrinsics'].inverse()           # b n 3 3
  E_inv = batch['extrinsics'].inverse()           # b n 4 4

Thanks a lot!

bradyz commented 2 years ago

If you don't have these camera parameters the model's performance would indeed decrease - Table 3 shows the model's performance decreases by several points with unknown extrinsics.

If your camera pose is guaranteed fixed with respect to the ego vehicle, the network could learn these parameters though and still perform well

duohaoxue commented 2 years ago

Thank you very much for your answers