Learning Oracle Attention for High-fidelity Face Completion
1. Motivation 人脸拥有丰富且微妙的纹理特征，不同的人的这些特征各不相同； 传统方法不能处理具有复杂结构和大规模缺失的图像，只能利用底层特征； 一些基于深度学习的方法忽视了不精确的 Attention分数所带来的影响。 2. Approach 2.1 Network Structure 整个网络可以分别为两部分生成器和判别器，生成器部分采用U-Net的结构，判别器采用了PatchGAN
相关文章
- 1. Learning disentangling and fusing networks for face completion under structured occlusions
- 2. Generative Face Completion
- 3. SaGAN:Generative Adversarial Network with Spatial Attention for Face Attribute Editing
- 4. Learning Residual Images for Face Attribute Manipulation
- 5. Similarity Metric Learning for Face Recognition2013
- 6. Geometry-Aware Face Completion and Editing
- 7. Transfer Learning for Item Recommendations and Knowledge Graph Completion
- 8. Face Paper：Face Attention Network: An Effective Face Detector for the Occluded Faces
- 9. 计算机视觉论文笔记四：Attention-Set based Metric Learning for Video Face Recognition
- 10. 《Multi-task Learning based Pre-trained Language Model for Code Completion》阅读
- 更多相关文章...
- • Swift for 循环 - Swift 教程
- • Scala for循环 - Scala教程
- • Java Agent入门实战（三）-JVM Attach原理与使用
- • Java Agent入门实战（一）-Instrumentation介绍与使用
相关标签/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。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. Learning disentangling and fusing networks for face completion under structured occlusions
- 2. Generative Face Completion
- 3. SaGAN:Generative Adversarial Network with Spatial Attention for Face Attribute Editing
- 4. Learning Residual Images for Face Attribute Manipulation
- 5. Similarity Metric Learning for Face Recognition2013
- 6. Geometry-Aware Face Completion and Editing
- 7. Transfer Learning for Item Recommendations and Knowledge Graph Completion
- 8. Face Paper：Face Attention Network: An Effective Face Detector for the Occluded Faces
- 9. 计算机视觉论文笔记四：Attention-Set based Metric Learning for Video Face Recognition
- 10. 《Multi-task Learning based Pre-trained Language Model for Code Completion》阅读