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InhwanBae / LMTrajectory

Official Code for "Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction (CVPR 2024)"
https://ihbae.com/publication/lmtrajectory/
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models for ETH-UCY in meter coordinates #11

Open DelinquentLeon opened 1 week ago

DelinquentLeon commented 1 week ago

Thanks for your work! I wonder if there are models pretrained for ETH-UCY in meter coordinates,cuz the models released online are in the name of xxx-pixel-multimodal-xxxx,or these can be also used for evaluating the ETH-UCY in meter coordinates?

InhwanBae commented 1 week ago

Hi @DelinquentLeon,

Thank you for your interest in our work!

The pretrained models are trained using pixel coordinates, but we project these coordinates into meter coordinates for evaluation. This way, our evaluations are directly comparable to other models that use meter coordinates. Therefore, You can directly evaluate the released models on ETH-UCY in meter coordinates, as the projection is part of the evaluation process.

https://github.com/InhwanBae/LMTrajectory/blob/4723b3943f3b8ed478b1abfa71dd0cabebbe2779/model/eval_accelerator.py#L187-L191

Let me know if you need any more clarification!

DelinquentLeon commented 13 hours ago

Thanks for your kind reply! But i meet some other problems when trying to train the model for SDD dataset. I wondered how is the _reference.png created, is it selected from a random frame? Or is it matter if i choose a random frame to generate the caption for SDD dataset.