Summary of Maskedmimic: Unified Physics-based Character Control Through Masked Motion Inpainting, by Chen Tessler et al.
MaskedMimic: Unified Physics-Based Character Control Through Masked Motion Inpainting
by Chen Tessler, Yunrong Guo, Ofir Nabati, Gal Chechik, Xue Bin Peng
First submitted to arxiv on: 22 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents MaskedMimic, a novel approach to crafting a single, versatile physics-based controller for character animation that supports diverse control modalities. The proposed method formulates physics-based character control as a general motion inpainting problem, training a single unified model to synthesize motions from partial (masked) motion descriptions. This approach learns a physics-based controller that provides an intuitive control interface without requiring tedious reward engineering for all behaviors of interest. The resulting controller supports a wide range of control modalities and enables seamless transitions between disparate tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a single, versatile virtual character that can dynamically adapt to complex scenes and compose diverse motions on demand, enabling more interactive and immersive experiences. |
