Motion4Motion: Motion Transfer Across Subjects at Inference
This work explores the motion transfer from one video to another, which is crucial in animation for diverse characters. Previously, video motion transfer has been largely explored between human and human-like characters, enabling a lot of applications in digital creation. However, these approaches encounter a main limitation. Specifically, related technical pipelines heavily rely on a predefined human skeleton structure and accordingly require skeleton-conditional model training. On the one hand, these methods are difficult to generalize to diverse characters, such as animals from different sp
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- PossiblePossibly related (embedding) · 47%huggingface/transformers →
- LinkedLinked via arxiv author · 85%Ling-Hao Chen →
“Motion4Motion: Motion Transfer Across Subjects at Inference”
- LinkedLinked via arxiv author · 85%Zixin Yin →
“Motion4Motion: Motion Transfer Across Subjects at Inference”
- LinkedLinked via arxiv author · 85%Duomin Wang →
“Motion4Motion: Motion Transfer Across Subjects at Inference”
- LinkedLinked via arxiv author · 85%Xianfang Zeng →
“Motion4Motion: Motion Transfer Across Subjects at Inference”
- LinkedLinked via arxiv author · 85%Gang Yu →
“Motion4Motion: Motion Transfer Across Subjects at Inference”
- PossiblePossibly related (embedding) · 47%jama1017/MoVer →