Research map / Image generation / Editing and style transfer
Adaptive Convolutions for Structure-Aware Style Transfer
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use global AdaIN statistics rather than AdaConv kernels | style transfer · Style transfer user study | content preservation preference: 93.9% | Helped |
| Predict adaptive convolution kernels from the style descriptor | style transfer · Style transfer user study | style structure preference: 92% | Helped |
| Replace global AdaIN modulation with AdaConv kernel prediction | style transfer · Style transfer user study | overall style transfer preference: 71.8% | Helped |
Closest papers by meaning
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- Style Injection in Diffusion: A Training-free Approach for Adapting Large-scale Diffusion Models for Style Transfer (CVPR 2024 · similarity 0.89)
- StyleStudio: Text-Driven Style Transfer with Selective Control of Style Elements (CVPR 2025 · similarity 0.87)
- ArtBank: Artistic Style Transfer with Pre-trained Diffusion Model and Implicit Style Prompt Bank (AAAI 2024 · similarity 0.87)
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