Human Motion Synthesis_ A Diffusion Approach for Motion Stitching and In-Betweening

Human motion generation is an important area of research in many fields. In this work, we tackle the problem of motion stitching and in-betweening. Current methods either require manual efforts, or are incapable of handling longer sequences. To address these challenges, we propose a diffusion model...

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Bibliographic Details
Published inarXiv.org
Main Authors Adewole, Michael, Giwa, Oluwaseyi, Favour Nerrise, Martins Osifeko, Oyedeji, Ajibola
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 10.09.2024
Subjects
Human motion
Human performance
Performance evaluation
Sequences
Stitching
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Summary:Human motion generation is an important area of research in many fields. In this work, we tackle the problem of motion stitching and in-betweening. Current methods either require manual efforts, or are incapable of handling longer sequences. To address these challenges, we propose a diffusion model with a transformer-based denoiser to generate realistic human motion. Our method demonstrated strong performance in generating in-betweening sequences, transforming a variable number of input poses into smooth and realistic motion sequences consisting of 75 frames at 15 fps, resulting in a total duration of 5 seconds. We present the performance evaluation of our method using quantitative metrics such as Frechet Inception Distance (FID), Diversity, and Multimodality, along with visual assessments of the generated outputs.
ISSN:2331-8422