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20242026
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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.CV2026

Echoes Over Time: Unlocking Length Generalization in Video-to-Audio Generation Models

Christian Simon, Masato Ishii, Wei-Yao Wang +8

Scaling multimodal alignment between video and audio is challenging, particularly due to limited data and the mismatch between text descriptions and frame-level video information.…

cs.CV2025

Schrodinger Audio-Visual Editor: Object-Level Audiovisual Removal

Weihan Xu, Kan Jen Cheng, Koichi Saito +10

Joint editing of audio and visual content is crucial for precise and controllable content creation. This new task poses challenges due to the limitations of paired audio-visual dat…

cs.CV2025

TalkCuts: A Large-Scale Dataset for Multi-Shot Human Speech Video Generation

Jiaben Chen, Zixin Wang, Ailing Zeng +8

In this work, we present TalkCuts, a large-scale dataset designed to facilitate the study of multi-shot human speech video generation. Unlike existing datasets that focus on single…

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…