Question about the codebase of detector (Detectron or tf-faster-rcnn) about ican HOT 5 CLOSED

1. Yes. I ran the official Caffe2 implementation of Detectron on HICO-DET dataset. The filename gives you the cue about the parameters, i.e. R-50-PFN_2x.

2. As for training, I didn't use anything from tf-faster-rcnn. Could you please specify in which line of my training code you found tf-faster-rcnn is involved? I will take a look at it. Thanks!

from ican.

1. Yes. I ran the official Caffe2 implementation of Detectron on HICO-DET dataset. The filename gives you the cue about the parameters, i.e. R-50-PFN_2x.
2. As for training, I didn't use anything from tf-faster-rcnn. Could you please specify in which line of my training code you found tf-faster-rcnn is involved? I will take a look at it. Thanks!

In lib/networks/iCAN_ResNet50_HICO.py, the implementation of backbone is similar to the one in tf-faster-rcnn, but I'm not sure whether they're exactly the same.

from ican.

@gaochen315 Sorry for my mistake, I've read your code carefully, and it seems that you've used a refined ResNet-50 (only stage 1 to stage 4) for feature extraction before the three streams. So I wonder whether the feature extraction network has been pre-trained on any datasets or it can be trained end-to-end during the training process of the whole model?

Thank you for your attention!

from ican.

The feature extraction network is initialized from tf-faster-rcnn's model (trained on COCO). It is not trained from scratch.

from ican.

The feature extraction network is initialized from tf-faster-rcnn's model (trained on COCO). It is not trained from scratch.

Thank you!

from ican.