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Thank you for your question. I did not report the timing comparison with FairMOT with Yolo v5s backbone in my paper. From my experiments, FairMOT with Yolo v5s backbone is faster than original FairMOT. However, the model still suffers from scalability and memory issues, resulting from using Re-ID network. As the number of people in the frame increases, the time taken to associate each detected object with the number of tracklets increases.
Therefore, LMOT is more preferable for realtime performance
Do you have timing comparison with FairMOT with Yolo v5s backbone? If they are similar, what makes LMOT more preferable?
Thank you
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