Interesting, but is it just me or does it seem overly jumpy?
I’m kind of impressed by how smooth it is, actually. If you watch videos of state-of-the-art object localization NNs, they tend to be EXTREMELY jumpy. These neural nets usually operate on only a single frame at a time, at least in the lower layers, so their predictions tend to jump around a lot from frame to frame (especially when the camera is moving!)
It worries me in general though, and I think that a higher level of consistently in the results of the parts of the image that don't significantly change between frames seems like a goal worth pursuing.
I also think that a deeper understanding of the mechanisms and techniques required to reduce jitter might offer some insights into ways of handling adversarial images.