May 4, 2024Open Access

Efficient Text-driven Motion Generation via Latent Consistency Training

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Authors

MHMengxian HuTongji University MZMinghao ZhuLiaoning Technical University XZXun ZhouBeijing Institute of Technology

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Implication

Randomized trial demonstrates improved performance in motion generation, suggesting reduced computational cost.

Key Points

The proposed model achieves state-of-the-art performance with a reduction of time cost below 10%.
Key evidence indicates motion generation efficacy improved via latent consistency training techniques and optimization.
Method analysis employs latent consistency training combined with diffusion models for effective motion generation refinement across benchmarks in human motion data sets and performance metrics available in under 10% computational time cost for inference steps used across various functions evaluated sequentially over iterations through sampling pipelines developed recently in literature and benchmarks used here in the study conducted through detailed experimentation phases with results compared against existing setups of similar design constraints worldwide across datasets investigated extensively over each benchmark location studied sequentially across analyses conducted collectively to highlight model efficacy through advanced design optimizations introduced on PF-ODE trajectories supported through systematic assessment frameworks to ensure accuracy in performance outcomes observed throughout designed studies collectively conducted through measuring effectiveness against state-of-art metrics established prior in the field often used for validation across significant domains of application in model performance evaluations conducted overall during assessments undertaken through comprehensive reporting mechanisms established historically across related outcomes achieved throughout established studies conducted.

Cite This Study

Hu et al. (2024) studied this question.

synapsesocial.com/papers/68e6b92bb6db64358763a377 https://doi.org/10.48550/arxiv.2405.02791

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Efficient Text-driven Motion Generation via Latent Consistency Training

Discussion

Member takes

Implication

Key Points

Cite This Study

Efficient Text-driven Motion Generation via Latent Consistency Training

Discussion

Member takes

Implication

Key Points

Cite This Study

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