Thank you for your great contribution. When checking the code for agentformer, I noticed the number of samples do not match that of Social-STGCNN and SGAN. Looking at these two latter codes, they only consider scenes where they contain more than one pedestrian. Is that also the case in your code and I have overlooked something? Looking at the samples that test.py outputs, some of them include only one pedestrian.
If this is true, would it be fair to compare against SGAN? Trajectron ++ also has the same train/test splits as SGAN.
Thank you for your great contribution. When checking the code for agentformer, I noticed the number of samples do not match that of Social-STGCNN and SGAN. Looking at these two latter codes, they only consider scenes where they contain more than one pedestrian. Is that also the case in your code and I have overlooked something? Looking at the samples that test.py outputs, some of them include only one pedestrian.
If this is true, would it be fair to compare against SGAN? Trajectron ++ also has the same train/test splits as SGAN.