NVIDIA1.79 млн
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Опубликовано 23 марта 2022, 16:59
With adversarial reinforcement learning, physically simulated characters can be developed that automatically synthesize lifelike and responsive behaviors.
A character is first trained to perform complex motor skills by imitating human motion data. Once the character has acquired a rich repertoire of skills, it can reuse those skills to perform new tasks in a natural, lifelike way.
This model then allows you to generate motions for new scenarios, without tedious manual animation or new motion data from real actors.
A character is first trained to perform complex motor skills by imitating human motion data. Once the character has acquired a rich repertoire of skills, it can reuse those skills to perform new tasks in a natural, lifelike way.
This model then allows you to generate motions for new scenarios, without tedious manual animation or new motion data from real actors.
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