Comments (2)
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
from cross_view_transformers.
Thank you very much for your answers
from cross_view_transformers.
Related Issues (20)
- error training HOT 1
- How long does it take to train the model?
- Geometric reasoning in cross-view attention
- How to train this for segmenting more than 2 classes? HOT 1
- Question about camera extrinsics
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- loss function mutation when training
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- visualize of attention
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from cross_view_transformers.