Facial Image Completion Using Bi-Directional Pixel LSTM
Structural features of facial images directly affect the performance of the image completion model. However, most existing work does not make full use of spatial dependence to extract features, and cause the semantics and structure of completion being inconsistent with the context. This paper addres...
Main Authors: | Xiulan Yu, Jiahao He, Zufan Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9007419/ |
Similar Items
-
Neural Feedback Text Clustering With BiLSTM-CNN-Kmeans
by: Yang Fan, et al.
Published: (2018-01-01) -
Make It Directly: Event Extraction Based on Tree-LSTM and Bi-GRU
by: Wentao Yu, et al.
Published: (2020-01-01) -
A Novel PPA Method for Fluid Pipeline Leak Detection Based on OPELM and Bidirectional LSTM
by: Lei Yang, et al.
Published: (2020-01-01) -
Automatically Query Active Features Based on Pixel-Level for Facial Expression Recognition
by: Zhe Sun, et al.
Published: (2019-01-01) -
Extended Global–Local Representation Learning for Video Person Re-Identification
by: Wanru Song, et al.
Published: (2019-01-01)