Why? Is there any remote need to generate scary faces? Or is it done just to have catchy PR title. I hope there is some real motivation to do this line of research.
Nice list, but there are too many papers like this and it is easy to get stuck in theory. I would suggest to grab some simple neural network (Darknet is great for that) code and read that first. If something does not make sense, find the theory from papers.
I wander how many people still implement their own networks as opposed to use these prepared frameworks. Or do you guys stick to single framework or use some sort of mixture of tools?
Thumb up for Qualcomm demo and Andrea Vedaldi presentation of MatConvNet presented at ICVSS 2015 summer school (not a conference). Both pieces made similar impression on me.
This guy wants to be super cool and cover just everything. Be kind, be super programmer, have tattoo, write blog ... Thinking about the post, I quite understand why people don't want to work with such superheroes. Kind will not make it if it is one other thing you want to be good at. Don't show off too much will do.
The article nicely illustrates the complexity present in a single image and I agree that we are far from automatically and fully understand images like this. I believe we would need to replicate the full brain to do that. But still, there are many interesting applications that are possible with state of the art computer vision. The question is whether state of the art is useful for industry, not whether the ultimate goal is close or far.