YOLOv3 odd detection behaviour vs YOLOv2

Here’s the same image put through YOLOv2COCO and then YOLOv3COCO respectively (threshold set at 0.4 and input resolution at 416x416 for both):

YOLOv3 does pick up the smaller people (as one would expect) - but for some reason it seems to predicting a much smaller bounding box than it should. I’ve done some experimenting and similar behavior is exhibited on quite a few images (sometimes the proper box appears and a smaller, inner one also appears - in this case, though, only the smaller one is appearing).

It’s possible that this is just due to a poor prediction on the model’s part, but my guess is that it isn’t and due to some problem with the NMS function (almost as if it’s doing non-minimal-suppression…if that’s a thing 😄 ) or other post processing step.

[taehoonlee]

@abagshaw, I confirmed the softmax issue and will revise the post processing with respect to the original one. Thank you!

[abagshaw]

@taehoonlee Problem solved! It’s working beautifully now as far as I can see. Thanks so much!