《Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization》論文解析
Ulyanov發現在風格遷移上使用IN效果比BN好很多，從他開始凡是風格遷移都離不開IN和其變種AdaIN，本文簡要介紹AdaIN這篇的原理。 下圖爲特徵圖張量，可以直觀看出BN，LN，IN，GN等規範化方法的區別。N爲樣本維度，C爲通道維度，H爲height，W即width，代表特徵圖的尺寸。 《Arbitrary Style Transfer in Real-tim
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相關文章
- 1. Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
- 2. 論文Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
- 3. 【風格遷移系列三】（Adain）Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization 論文解讀
- 4. Arbitrary Style Transfer with Deep Feature Reshuffle
- 5. 【風格遷移】Adaptive Instance Normalization（AdaIN）
- 6. AdaptIS: Adaptive Instance Selection Network
- 7. Image style transfer
- 8. 基於《Arbitrary Style Transfer with Style-Attentional Networks》的視頻風格遷移
- 9. 【風格遷移系列二】Fast Patch-based Style Transfer of Arbitrary Style 論文解讀
- 10. 論文Controlling Perceptual Factors in Neural Style Transfer