This AI Learned Some Crazy Fighting Moves! 🥊

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This AI Learned Some Crazy Fighting Moves! 🥊

Two Minute Papers 02.10.2021 940 271 просмотров 31 085 лайков

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❤️ Check out Perceptilabs and sign up for a free demo here: https://www.perceptilabs.com/papers 📝 The paper "Neural Animation Layering for Synthesizing Martial Arts Movements" is available here: https://github.com/sebastianstarke/AI4Animation/blob/master/Media/SIGGRAPH_2021/Paper.pdf https://github.com/sebastianstarke/AI4Animation 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Benji Rabhan, Bryan Learn, Christian Ahlin, Eric Haddad, Eric Martel, Gordon Child, Ivo Galic, Jace O'Brien, Javier Bustamante, John Le, Jonas, Kenneth Davis, Klaus Busse, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Mark Oates, Michael Albrecht, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Ramsey Elbasheer, Steef, Taras Bobrovytsky, Thomas Krcmar, Timothy Sum Hon Mun, Torsten Reil, Tybie Fitzhugh, Ueli Gallizzi. If you wish to appear here or pick up other perks, click here: https://www.patreon.com/TwoMinutePapers Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Meet and discuss your ideas with other Fellow Scholars on the Two Minute Papers Discord: https://discordapp.com/invite/hbcTJu2 Károly Zsolnai-Fehér's links: Instagram: https://www.instagram.com/twominutepapers/ Twitter: https://twitter.com/twominutepapers Web: https://cg.tuwien.ac.at/~zsolnai/ #gamedev

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Dear Fellow Scholars, this is Two Minute Papers with Dr. Károly Zsolnai-Fehér. Today we are going to see if a virtual AI character can learn, or perhaps even invent these amazing signature moves. And this is a paper that was written by Sebastian Starke and his colleagues. He is a recurring scientist on this series, for instance, earlier he wrote this magnificent paper about Dribbling AI characters.

Locomotion Control

Look. The key challenge here was that we were given only 3 hours of unstructured motion capture data. That is next to nothing, and from this next to nothing, it not only learned these motions really well, but it could weave them together, even when a specific movement combination was not present in this training data.

Dribble Maneuvers

But, as these motions are created by human animators, and may show at least three problems. One, the training data may contain poses that don’t quite adhere to the physics of a real human character. Two, it is possible that the upper body does something that makes sense, the lower body also but the whole thing, put together, does not make too much sense anymore. Or, three, we may have these foot sliding artifacts that you see here. These are more common than you might first think, here is an example of it from a previous work, and, look, nearly all of the previous methods struggle with it. Now, this new work uses 20 hours of unstructured training data.

Neural Animation Layering Framework

Now, remember, the previous one only used 3, so we rightfully expect that by using more information, it can also learn more. But the previous work was already amazing, so, what more can we really expect this new one to do? Well, it can not only learn these motions, weave together these motions like previous

Motion Layering

works, but, hold on to your papers, because it can now also come up with novel moves as

Novel Allock Sequences

well! Wow. This includes new attacking sequences, and combining already existing attacks with novel footwork patterns. And it does all this spectacularly well. For instance, if we show it how to have its guard up, and how to throw a punch, what will it learn? Get this, it will keep its guard up while throwing that punch. And it not only does that in a realistic, fluid movement pattern, but it also found out about something that has strategic value. Same with evading an attack with some head movement and counterattacking. Loving it. But how easy is it to use this? Do we need to be an AI scientist to be able to invoke these amazing motions? Well, if you have been holding on to your papers so far, now, squeeze that paper, and look here. Wow. You don’t need to be an AI scientist to play with this! Not at all! All you need is a controller to invoke these beautiful motions. And all this runs in real time. My goodness! For instance, you can crouch down and evade a potential attack by controlling the right stick, and launch a punch in the meantime. Remember, not only both halves have to make sense separately, the body motion has to make sense as a whole. And it really does, look at that. And here comes the best part, you can even assemble your own signature attacks, for instance, perform that surprise spinning backfist, an amazing spin kick, and, yes!

Crane Kick

You can even go full Karate Kid with that crane kick. And as a cherry on top, the characters can also react to the strikes, clinch, or even try a takedown. So, with that, there we go, we are again, one step closer to having access to super realistic motion techniques for virtual characters, and all we need for this is a controller. And remember, all this already runs in real time! Another amazing SIGGRAPH paper from Sebastian Starke. And get this, he is currently a 4th year PhD student and already made profound contributions to the industry. Huge congratulations on this amazing achievement. What a time to be alive! Thanks for watching and for your generous support, and I'll see you next time!

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