Raw CSD cosine similarity produces negative discrimination gaps for many artists and does not support absolute style-fidelity interpretation, but CSLS readout on frozen backbones reduces failures and improves AUC.
InstantStyle-Plus: Style transfer with content-preserving in text-to-image generation
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
representative citing papers
DiLAST optimizes 3D latents via guidance from a 2D diffusion model to enable generalizable style transfer for OOD styles in 3D asset generation.
Rule-based and learning-based algorithms simplify dance motions to help novices learn more effectively while maintaining naturalness and style.
A training-free method modifies diffusion model sampling with differentiable Sliced 1-Wasserstein distance for color-conditional image generation.
CraftGraffiti applies LoRA-tuned diffusion transformers followed by identity-augmented self-attention and CLIP-guided pose extension to generate graffiti while preserving facial features.
citing papers explorer
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When Style Similarity Scores Fail: Diagnosing Raw CSD Cosine in Artist-Style Evaluation
Raw CSD cosine similarity produces negative discrimination gaps for many artists and does not support absolute style-fidelity interpretation, but CSLS readout on frozen backbones reduces failures and improves AUC.
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Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion
DiLAST optimizes 3D latents via guidance from a 2D diffusion model to enable generalizable style transfer for OOD styles in 3D asset generation.
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Make it Simple, Make it Dance: Dance Motion Simplification to Support Novices' Dance Learning
Rule-based and learning-based algorithms simplify dance motions to help novices learn more effectively while maintaining naturalness and style.
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Color Conditional Generation with Sliced Wasserstein Guidance
A training-free method modifies diffusion model sampling with differentiable Sliced 1-Wasserstein distance for color-conditional image generation.
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CraftGraffiti: Exploring Human Identity with Custom Graffiti Art via Facial-Preserving Diffusion Models
CraftGraffiti applies LoRA-tuned diffusion transformers followed by identity-augmented self-attention and CLIP-guided pose extension to generate graffiti while preserving facial features.