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Age Progression and Regression with Spatial Attention Modules(AAAI20)
時間 2020-12-30
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Method Problem Formulation 定義young face image爲 I y \mathbf{I}_y Iy,對應的age爲 α y \bm{\alpha}_y αy,是一個one-hot向量 給定目標age α o \bm{\alpha}_o αo(要求 α o > α y \bm{\alpha}_o\gt\bm{\alpha}_y αo>αy),我們希望學習一
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相關文章
1.
The issus in Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE)
2.
SaGAN:Generative Adversarial Network with Spatial Attention for Face Attribute Editing
3.
linear regression and logistic regression with pytorch
4.
Paper Reading -- CSA-MSO3DCNN: Multiscale Octave 3D CNN with Channel and Spatial Attention
5.
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6.
TextSpotter with Explicit Alignment and Attention
7.
Regression with scikit-learn
8.
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10.
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