Re:Using neural networks to upscale a famous 1896 video to 4...
by tachyonbeam on Wednesday February 05, 2020 @06:25PM
(#22251956)
I work in deep learning research. In my opinion, pose estimation with one human centered in a frame is nowhere near the level of difficulty of constructing an accurate model of a complex a scene with multiple people and moving objects of various sizes. For instance, it wouldn't be so hard to detect that there is a train in this video, but to do upscaling correctly, you need a 3D model of this specific train. Yes, there exist deep learning models that try to do 3D reconstruction, and so far, I haven't seen anything that works robustly. Combining this information with an upscaling model is another challenge. It's not as easy as just plugging components together.
Each one of the items you've listed has been severally accomplished by ML to varying levels of success (baseline being "workable", and more progress is being made.) I probably would have found better references had I spent longer than 5 minutes searching
1. https://www.youtube.com/watch?v=AGm3hF_BlYM
2. https://www.theverge.com/2019/12/9/20999646/google-arcore-au...
3. Same as 2 :-). AR Occlusion requires both. Additionally many recent phones use ML models to fake depth-of-field; boundary between foreground objects has to be detected
4. Also see 2; Augmented Reality is hard. bonus: https://www.awn.com/animationworld/how-klaus-uniquely-combin...