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HarshayuGirase / Human-Path-Prediction

State-of-the-art methods for human trajectory forecasting. Contains code for papers published at ECCV 2020 and ICCV 2021.
MIT License
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[Solved] Reproduced ETH Result #53

Closed SaoDiSengA closed 1 year ago

SaoDiSengA commented 1 year ago 
    Hi @karttikeya

This is to confirm that indeed 170 does benefit.

Here is a new notebook in which I am training ETH

https://colab.research.google.com/drive/1OdVwL3CM-_f-T3HlHyY3B2IaTDiKmprs?usp=sharing

This notebook has some differences from code in your repository because of the data preparation part. Everything is in the notebook itself including downloading of datasets etc.

Above to reproduce similar results as paper. Some of the runs produced even a better number.

Would appreciate if you have a cursory look to see I am not doing anything wrong as even though I managed to reproduce your numbers with machine learning it is easy to get fooled.

Again I want to thank you for the time you spent answering the questions; I am very happy that the results of your paper can be reproduced. This is an achievement in itself and indeed a good job on your part and your co-authors.

Regards Kapil

Originally posted by @ksachdeva in https://github.com/HarshayuGirase/Human-Path-Prediction/issues/7#issuecomment-705223578

karttikeya commented 1 year ago

Hi @SaoDiSengA ,

Thanks for your message and confirming the reproduction and sharing the notebook.

Here is my copy of the same notebook (for redundancy): ETH result

This would help future users to be able to follow a 3rd party reproduction.

SaoDiSengA commented 1 year ago

Hi @SaoDiSengA ,

Thanks for your message and confirming the reproduction and sharing the notebook.

Here is my copy of the same notebook (for redundancy): ETH result

This would help future users to be able to follow a 3rd party reproduction.

but,i want to get other npz files,like ucy,sdd