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cs.CV2026
Odoriko: A Shape-Aware Multimodal Diffusion Framework for Human Motion
Dongseok Shim, Julian Tanke, Kengo Uchida +5
Human motion generation has been widely studied across diverse input modalities, text, music, and video, and recent efforts have unified these into single multimodal frameworks. Ho…
cs.CV2025
Dyadic Mamba: Long-term Dyadic Human Motion Synthesis
Julian Tanke, Takashi Shibuya, Kengo Uchida +2
Generating realistic dyadic human motion from text descriptions presents significant challenges, particularly for extended interactions that exceed typical training sequence length…
cs.CV2025
MoLA: Motion Generation and Editing with Latent Diffusion Enhanced by Adversarial Training
Kengo Uchida, Takashi Shibuya, Yuhta Takida +4
In text-to-motion generation, controllability as well as generation quality and speed has become increasingly critical. The controllability challenges include generating a motion o…