PIEPredict vs. SF-GRU about piepredict HOT 2 CLOSED

Hi,

Thanks for your comments. I think all the points you have made are very valid and worth trying. To answer your questions:
1- That certainly is one possibility. The data is not balanced and the network does favor the more represented class.
2- I believe it does. We have done some experimentations on that in one of our upcoming papers and saw its benefit in action classification
3- Regarding the dataset, training of the intention model can always be done on PIE and then just be used as part of the network on any other datasets. Regarding action for trajectory, Yes can definitely benefit trajectory prediction. This was highlighted in some recent publications at CVPR in the context of surveillance. The authors showed that activity recognition can improve trajectory prediction.
4- I totally agree with you. Intention in the framework we presented in our paper can be learned alongside trajectories. One reason why we did it in the way presented in the paper is that the intention data should resemble the conditions in which we ran our human experiments for the ground truth data to be valid. For trajectory prediction, however, we do not have such restrictions, therefore we can train it on many more samples. In this context, one could fine-tune the intention network at the end as part of the final model. I also agree with you, intention can also be formulated as a separate task beside trajectory instead of an input to the network, i.e. formulate it into a multi-task learning problem. I believe many variations of this should be examined. We only presented one of many possibilities.

from piepredict.

Hi again,

Thank you for your feedback! I'll follow your work closely :)

from piepredict.