#style-transfer2 articles

2 articles

AIBullisharXiv – CS AI · Feb 277/105

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VQ-Style: Disentangling Style and Content in Motion with Residual Quantized Representations

Researchers have developed VQ-Style, a new AI method that uses Residual Vector Quantized Variational Autoencoders to separate style from content in human motion data. The technique enables effective motion style transfer without requiring fine-tuning for new styles, with applications in animation, gaming, and digital content creation.

AIBullisharXiv – CS AI · 6d ago6/104

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TP-Blend: Textual-Prompt Attention Pairing for Precise Object-Style Blending in Diffusion Models

Researchers introduced TP-Blend, a training-free framework for diffusion models that enables simultaneous object and style blending using two separate text prompts. The system uses Cross-Attention Object Fusion and Self-Attention Style Fusion to produce high-resolution, photo-realistic edits with precise control over both content and appearance.