TY  - JOUR
TI  - Human Motion Diffusion Model (MDM)
AU  - Tevet, G.
AU  - Raab, S.
AU  - Gordon, B.
AU  - Shafir, Y.
AU  - Cohen-Or, D.
AU  - Bermano, A. H.
PY  - 2023
DA  - 2023///
JO  - ICLR 2023 (Oral)
AB  - Tevet et al. (2022, published ICLR 2023 Oral) introduce the Motion Diffusion Model, a transformer-based diffusion model that operates directly on motion sequences and accepts conditioning from text prompts, action labels, or partial keyframes. The approach produces diverse, naturalistic human motions without requiring a motion prior or complex post-processing. As the founding paper in text-to-motion diffusion, MDM established the architecture underlying a generation of motion-generation tools that are entering character animation and virtual-production pipelines.
KW  - character-animation
KW  - motion-synthesis
KW  - generative-ai
UR  - https://arxiv.org/abs/2209.14916
LA  - en
ER  -