Simon Clavet @profbof
Animation Programmer Montreal Joined July 2009-
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@belinghy Yes. Along with @anorangeduck, @_Quazi_, and Felix Harvey, who performed the KungFu routine. To be perfectly clear, we are nerds, not athletes.
@siyuanhuang95 The mocap data they used is dance1subject2 of Lafan1 public animation dataset. I was in the suit. Surreal.
Simon Clavet is bringing his talent to TiMi Studio Group! A pioneer in procedural animation for gaming, he now joins our TiMi Montreal team to help us get our unannounced AAA open world multiplayer project in the hands of gamers worldwide. #montreal #gamedev #videogameindustry
@anorangeduck @RH_Hagdahl One thing I tried was to compute pos/vel distance 150ms ahead in current and candidate anims. So we minimise mismatch in the middle of the 300ms blend instead of the start.
How can we measure the cost of transitioning between two different animations? In this blog post I propose a solution based on the assumption of inertialization blending - involving (as usual) some playing around with spring equations! theorangeduck.com/page/inertiali…
A couple years ago I was dancing on 'uptown funk' in a mocap suit with @anorangeduck and @_Quazi_. The goal was to find a way to play any move on a non-cheating ragdoll (or a real robot). Good job guys. It worked.
I've just added a basic implementation of Learned Motion Matching to my previous Motion Matching demo. Hopefully useful to anyone working on this stuff. Results aren't visually any different (as intended), but still cool to see LMM running in the browser! github.com/orangeduck/Mot…
Supertrack: train a ragdoll to balance and play hours of difficult mocap by gradient descent on smooth/learned/differentiable physics. This changes everything.
Excited to share our latest work with Levi Fussell @HwTheFrondsFold and Kevin Bergamin @_Quazi_ - SuperTrack: Motion Tracking for Physically Simulated Characters using Supervised Learning. For a quick explanation check out this blog post: (1/4) montreal.ubisoft.com/en/supertrack-…
.@ZivaDynamics presented a machine learning-based system that converts character head meshes into real-time puppets capable of expressing over 72,000 facial shapes within an hour. The video is a real-time demo running in UE5 80.lv/articles/ziva-… #animation #3dart #gamedev
I really can't tell if this is real or fake. That's a milestone.
Finishing up this quick project with a short animation test. Kept the rig simple and only with controls I needed for this test #portraiture #blackbeauty #digitalart #blackpower #portrait #lighting #digitalhuman #animationtest
Another article - this time on joint limits, and how we can automatically compute them from data. theorangeduck.com/page/joint-lim… I've also added interactive web demos for this article and my previous article on code vs data driven displacement - much more fun to play with!
@olafurw You should also mention how redondancy can help a lot.
@olafurw You should also mention how redondancy can help.
@anorangeduck This code will be very useful. And it's MIT licensed, so we're allowed to copy paste it anywhere. Thank you Daniel you are the MVP.
This blog post is an important contribution. Go read it.
Another blog post on animation programming fundamentals, and today it's a big one - code vs data driven displacement - or how we can move a character around a game world in a way which is both responsive and realistic. theorangeduck.com/page/code-vs-d…
@anorangeduck Turns out I just live coded a simple motion matching setup. Trying to keep it extensible but still cache friendly. youtube.com/watch?v=jcpIrw…
@anorangeduck Motion matching is a nice example where cache is the most important thing to keep in mind. It is not the place to get fancy with dynamic arrays. Candidate frames are just rows in a big rectangle of numbers, and gameplay searches for the closest row.
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