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> I think many people will be very uncomfortable with such motion very quickly So... I think OP's point stands. (impressive, surpasses human/algorithmic animat
by netcan 3y ago
> I think many people will be very uncomfortable with such motion very quickly
So... I think OP's point stands. (impressive, surpasses human/algorithmic animation thus far).
You're also right. There are "tells." But, a tell isn't a tell until we've seen it a few times.
Jaron Lanier makes a point about novel technology. The first gramophone users thought it sounded identical to live orchestra. When very early films depicting a train coming towards a camera, and people fell out of their chairs... Blurry black and white, super slow frame rate projected on a bedsheet.
Early 3d animation was mindblowing in the 90s. Now it seems like a marionette show. Well... I suppose there was a time when marionette shows were not campy. They probably looked magic.
It seems we need some experience before we internalize the tells and it starts to look fake. My own eye for CG images seems to improving faster then the quality. We're all learning to recognize GPT generated text. I'm sure these motion captures will look more fake to us soon.
That said... the fact that we're having this discussion proves that what we have here is "novel." We're looking at a breakthrough in motion/animation.
Also, I'm not sure "real" is necessary. For games or film what we need is rich and believable, not real.
- Jensson 3y ago> You're also right. There are "tells." But, a tell isn't a tell until we've seen it a few times. Once you have seen a few you can tell instantly. They all move at 2 keyframes per second, that makes all movements seem alien and everything in an image moves strangely in sync. The dog moves in slow motion since they need more keyframes etc. That street some looks like they move in slow motion and others not. People will quickly learn to notice those issues, they aren't even subtle once you are aware of them, not to mention the disappearing things etc. And that wouldn't be very easy to fix, they need to train it on keyframes because training frame by frame is too much. But that should make this really easy for others to replicate. You just train on keyframes and then train a model to fill in between keyframes, and you get this. It has some limitations as we see with movement keeping the same pace in every video, but there are a lot of cool results from it anyway.
- kurthr 3y agoI have a friend who has worked on many generations of video compression over the last 20 years. He would rather watch a movie on film without effects than anything on a TV or digital theater. He's trained himself to spot defects and now even with the latest HEVC H.265 he finds it impossible to enjoy. It's artifacts all the way down and the work never ends. At the superbowl he was obsessed with blocking for fast objects, screen edge artifacts, flat field colors, and something with the grass. Luckily, I think he'll retire sooner than later, and maybe it will get better then.