Research map / Label-efficient and robust learning / Domain adaptation and generalization
In the Light of Feature Distributions: Moment Matching for Neural Style Transfer
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use CMD instead of the strongest competing method, Gatys | Neural style transfer · NST user study | votes: 533 -> 587 | Helped |
| Add the fifth-order central moment to the style loss (ablation) | CMD style transfer · Qualitative style transfer | visible style elements | Helped |
| Use odd moments to modulate brightness and contrast (ablation) | CMD style transfer · Qualitative style transfer | brightness and contrast control | Helped |
| Use even moments to affect colors and high-frequency texture (ablation) | CMD style transfer · Qualitative style transfer | color and high-frequency texture | Helped |
| Increase the content-loss weight α (ablation) | CMD style transfer · Qualitative style transfer | content preservation | Helped |
| Increase the learning rate (ablation) | CMD style transfer · Qualitative style transfer | content preservation | Hurt |
Closest papers by meaning
- Image Style Transfer Using Convolutional Neural Networks (CVPR 2016 · similarity 0.89)
- A Flexible Convolutional Solver for Fast Style Transfers (CVPR 2019 · similarity 0.89)
- Adaptive Convolutions for Structure-Aware Style Transfer (CVPR 2021 · similarity 0.89)
- Z*: Zero-shot Style Transfer via Attention Reweighting (CVPR 2024 · similarity 0.87)
- Style Injection in Diffusion: A Training-free Approach for Adapting Large-scale Diffusion Models for Style Transfer (CVPR 2024 · similarity 0.87)
- AesFA: An Aesthetic Feature-Aware Arbitrary Neural Style Transfer (AAAI 2024 · similarity 0.87)
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