arXiv Open Access 2024

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

Michael Adewole Oluwaseyi Giwa Favour Nerrise Martins Osifeko Ajibola Oyedeji
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Abstrak

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.

Topik & Kata Kunci

Penulis (5)

M

Michael Adewole

O

Oluwaseyi Giwa

F

Favour Nerrise

M

Martins Osifeko

A

Ajibola Oyedeji

Format Sitasi

Adewole, M., Giwa, O., Nerrise, F., Osifeko, M., Oyedeji, A. (2024). Human Motion Synthesis_ A Diffusion Approach for Motion Stitching and In-Betweening. https://arxiv.org/abs/2409.06791

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Tahun Terbit
2024
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en
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arXiv
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