SaGAN:Generative Adversarial Network with Spatial Attention for Face Attribute Editing
#Problem Traditional GAN methods directly operate on the whole image, and inevitably change the attribute-irrelevant regions The performance of traditional regression methods heavily depends on the pa
相關文章
- 1. SC-FEGAN: Face Editing Generative Adversarial Network with User’s Sketch and Color
- 2. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORK
- 3. Spatial Attention Network for Scene Parsing
- 4. Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction
- 5. Age Progression and Regression with Spatial Attention Modules（AAAI20）
- 6. STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing（CVPR19）
- 7. Face Aging with Contextual Generative Adversarial Nets
- 8. Face Paper：Face Attention Network: An Effective Face Detector for the Occluded Faces
- 9. Finding Tiny Faces in the Wild with Generative Adversarial Network
- 10. Learning Oracle Attention for High-fidelity Face Completion
- 更多相關文章...
- • C# 特性（Attribute） - C#教程
- • Swift for 循環 - Swift 教程
- • 爲了進字節跳動，我精選了29道Java經典算法題，帶詳細講解
- • Flink 數據傳輸及反壓詳解
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. SC-FEGAN: Face Editing Generative Adversarial Network with User’s Sketch and Color
- 2. FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORK
- 3. Spatial Attention Network for Scene Parsing
- 4. Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction
- 5. Age Progression and Regression with Spatial Attention Modules（AAAI20）
- 6. STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing（CVPR19）
- 7. Face Aging with Contextual Generative Adversarial Nets
- 8. Face Paper：Face Attention Network: An Effective Face Detector for the Occluded Faces
- 9. Finding Tiny Faces in the Wild with Generative Adversarial Network
- 10. Learning Oracle Attention for High-fidelity Face Completion