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Deep learning models that output character joint rotations in real-time for game engines.
Distinct from Neural Network Execution Engines: Candidates focus on visualizing neural networks or general training, not using them as the runtime driver for character joints.
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AI4Animation is a deep learning motion controller and framework for generating biped and quadruped locomotion from motion capture data. It provides a system for training and executing neural networks to drive real-time character animations within Unity. The project features a neural animation blending system that synthesizes novel movements by mixing unaligned motion sources using learned manifolds. It also includes a real-time inverse kinematics solver for computing joint positions based on target goals and scene geometry. The toolset covers motion capture data processing, including the imp
Executes trained deep learning models within a game engine to generate character joint rotations based on real-time inputs.