《Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization》论文解析
Ulyanov发现在风格迁移上使用IN效果比BN好很多，从他开始凡是风格迁移都离不开IN和其变种AdaIN，本文简要介绍AdaIN这篇的原理。 下图为特征图张量，可以直观看出BN，LN，IN，GN等规范化方法的区别。N为样本维度，C为通道维度，H为height，W即width，代表特征图的尺寸。 《Arbitrary Style Transfer in Real-tim
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相关文章
- 1. Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
- 2. 论文Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
- 3. 【风格迁移系列三】（Adain）Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization 论文解读
- 4. Arbitrary Style Transfer with Deep Feature Reshuffle
- 5. 【风格迁移】Adaptive Instance Normalization（AdaIN）
- 6. AdaptIS: Adaptive Instance Selection Network
- 7. Image style transfer
- 8. 基于《Arbitrary Style Transfer with Style-Attentional Networks》的视频风格迁移
- 9. 【风格迁移系列二】Fast Patch-based Style Transfer of Arbitrary Style 论文解读
- 10. 论文Controlling Perceptual Factors in Neural Style Transfer