Is it possible to make an object detector from scratch?

This post describe the flatten function I use on convs outputs (flatten_conv).
The problems is that I don’t see (I can’t find someone who says that also) a good result like the one I could get using tensorflow pretrained models.
The last thing is that I’m not sure if I’m taking pretrained models, following pascal-multi notebook doesn’t seems to do it:

  • f_model = resnet34
  • head_reg4 = SSD_MultiHead(k, -4.)
  • models = ConvnetBuilder(f_model, 0, 0, 0, custom_head=head_reg4)
  • learn = ConvLearner(md, models)

I tried with resnet34(pretrained=True) but then I get different errors when I try to train.

I assume the answer is a no, actual results on object detectors are quite bad and it’s still behind others frameworks in transfer learning?