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Hi, I have one question regarding the features for the deep association metric on DeepSort. I've noticed you used the CNN to get the features used in DeepSort wich was trained in the MARS dataset. This dataset is meant for person re-identification. Then my question is: How do you deal with object of different classes? I mean, do you use the same network (trained for person re-identification) to generate the deep feature descriptor of objects such as cars?
Thanks in advance!
The text was updated successfully, but these errors were encountered:
We used the same network as we observed fairly decent tracking results without re-training the network. Maybe 1-2 % improvement occurs by re-training, but we didn't require it.
Hi @rohanchandra30,
Thanks for your reply, interesting results. I'm trying to use deepsort with COCO objects, but my experiments show that the original feature extraction network trained con MARS is not able to individually differentiate between different objects. From my experience, it seems to rely a lot on the color of the object, and for a lot of objects that's not useful.
Hi, I have one question regarding the features for the deep association metric on DeepSort. I've noticed you used the CNN to get the features used in DeepSort wich was trained in the MARS dataset. This dataset is meant for person re-identification. Then my question is: How do you deal with object of different classes? I mean, do you use the same network (trained for person re-identification) to generate the deep feature descriptor of objects such as cars?
Thanks in advance!
The text was updated successfully, but these errors were encountered: