[TheFragenTaken]

Some of these NN models are quite heavy, and I'd argue, overkill for bounded applications, like "just" segmenting people from a video stream. People have built simplistic naive bayes based models before NN's were popular, using relatively few features, and applying a Kalman filter to track across frames, that could run on Pentium processors in the 2000's and 10's.

[IshKebab]

They mentioned reliability so I think they want the performance of current ML models, not what we had 10-20 years ago, which was terrible.

[atoav]

I tried other, non-ML solutions but they were too unreliable in that they produced a huge number of false positives and false negatives under the unpredictable circumstances I have to operate under. They were quite performant tho and I imagine in the right circumstances they might achieve good results.