Researchers have developed a new framework called CMC for generating realistic human motions that accurately follow specified trajectories and textual descriptions. Existing methods struggle with conflicting conditions and inconsistent motion representations. CMC addresses this by decoupling the process into two stages: trajectory control and motion completion, ensuring stable trajectory following and high-quality full-body motion synthesis. The framework also incorporates a Selective Inpainting Mechanism to improve training with limited data, achieving state-of-the-art results on benchmark datasets. AI
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IMPACT Introduces a novel approach to multimodal condition coordination for realistic human motion synthesis, potentially improving applications in animation and robotics.
RANK_REASON The cluster contains an academic paper detailing a new method for human motion generation. [lever_c_demoted from research: ic=1 ai=1.0]