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Hi @MoonBlvd,
I am trying to train the BiTraP model on the nuScenes dataset and replicate the results stated in section III of the Supplementary File in your paper. I have a few questions on the setup used for nuScenes, since my reproduction results are different from the 0.58 FDE reported in the paper.
- How was the nuScenes dataset preprocessed for pedestrian-only? (We used the preprocessing code from Trajectron++, and we removed code that references vehicle to produce a pedestrian-only nuScenes pickle).
- How many frames are used for observation? (We used 8 frames for observation and 8 frames for prediction).
Another issue is that our training results and testing results are drastically different. Following the instructions in this repo's README, we used the files under https://github.com/umautobots/bidireaction-trajectory-prediction/tree/main/tools for training and testing. For training, we saw the FDE drop to around 0.39, but when running test.py, the FDE was around 2.07. Have you run into this issue before?
Thanks in advance!
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