

Momask
Overview :
MoMask is a model for text-driven 3D human motion generation. It employs a hierarchical quantization scheme to represent human motion as multi-layer discrete motion tokens with high fidelity details. MoMask utilizes two distinct bidirectional Transformer networks for generation, predicting motion tokens from text input. This model outperforms existing methods in the text-to-motion generation task and can seamlessly be applied to related tasks such as text-guided temporal repair.
Target Users :
MoMask can be used to generate 3D human motion, which can be applied to text-guided temporal repair tasks.
Features
Generates 3D human motion based on text input
Uses a hierarchical quantization scheme to represent motion details
Applicable to text-guided temporal repair
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