I've just given this a go, with very little work I was able to produce a near seamless mask which was able to adapt to dynamic and changing pose - interesting s

I've just given this a go, with very little work I was able to produce a near seamless mask which was able to adapt to dynamic and changing pose - interesting stuff. The main drawback I observed was computation speed, most edits required >20 seconds of loading/buffering (with a 1Gbps internet connection). I presume the computation occurs on their own servers, so with beefier hardware the performance could be increased, however my intuition is that the app would perform faster if running natively (rather than a shared resource quota on a remote server). In this regard, the lack of performance could be a major productivity killer, my hypothesis is that it is the video processing/manipulation which is taking a long time (and not the model classification). Many companies have tackled this problem space with completely video transcoding chips (such as YouTube), however this generally still incurs long periods of waiting.