learned-motion-synthesis technique sourced
Learned kinematic motion synthesis
Neural networks generate or compress kinematic character animation, as in Ubisoft's learned motion matching, EA's HyperMotion, and inZOI's motion extraction from uploaded video.
mechanism
Motion matching picks the next pose by searching a database of mocap frames for the best match to a query of current pose and desired trajectory. Learned motion matching replaces the database with three small networks: a Decompressor that maps a feature vector to a full pose, a Stepper that advances features one frame, and a Projector that maps a query to the nearest valid features, giving nearly identical output at constant CPU cost. HyperMotion trains a model on frames of full-team match capture to generate transitions in real time. Video-to-motion tools estimate 3D poses from ordinary video and retarget them onto a game rig. No physics is simulated.
limitations
- Kinematic output ignores physics, so characters still clip or float when the environment differs from the training motion.
- Learned motion matching saves memory but not per-character CPU time, which still limits crowd counts.
- Video-to-motion quality depends on the uploaded footage; occlusion and camera motion produce artifacts that the game must filter or let players discard.
appears in
the paper, 4 sections · 1 chapter · 2 episodesrelations
3 stored edges
Direct avatar control
Motion-matching-quality responsive locomotion fits in a few MB of weights, making it affordable on memory-constrained platforms and for more character types.
Generative content on demand
Players author new character motions from their own video (inZOI), so the animation set available to life-sim characters is no longer fixed by the studio's mocap library.
claims
4 with sourcesLearned motion matching shrank a 590 MB motion matching locomotion system to about 17 MB of weights (8.5 MB with 16-bit quantization), about 70 times smaller, with nearly identical output and constant CPU cost.
FIFA 22's HyperMotion used a machine learning algorithm over more than 8.7 million frames of 22-player match capture to generate player animation in real time, on PS5, Xbox Series X/S, and Stadia only.
inZOI lets players create character motions by uploading video files, disclosed as an AI-assisted feature.
Unreal Engine ships database motion matching through its Pose Search plugin, the non-learned baseline that learned motion matching compresses.