Open DelinquentLeon opened 1 month 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.
Let me know if you need any more clarification!
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.
Hi @DelinquentLeon,
For the SDD dataset, I used the same reference image provided in YNet. The _reference.png
file is identical to the reference.jpg
found in the annotation folder of the original SDD dataset. Since the SDD videos are static, selecting a random frame should not cause any issues in generating the caption.
Thanks for your kind reply! I also wondered if you directly used the data file train_trajnet.pkl and test_trajnet.pkl from Y-Net for training and evaluating,cuz i meet some difficulties when preprocessing the SDD dataset,especially aligning the coordinates with the reference picture
Additionally,could you please release the pretrained model on SDD dataset
Hi @DelinquentLeon,
Unfortunately, I currently don't have the code and pretrained model for the SDD dataset available at the moment. Due to frequent requests, I'm considering a reimplementation it later this year. You can find more details about the SDD implementation in this issue #7.
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?