Generative face alignment through 2.5D active appearance models-Reference-Cited by-同舟云学术

Generative face alignment through 2.5D active appearance models

Published:2013-03 Issue:3 Volume:117 Page:250-268
ISSN:1077-3142
Container-title:Computer Vision and Image Understanding
language:en
Short-container-title:Computer Vision and Image Understanding

Author:

Martins Pedro,Caseiro Rui,Batista Jorge

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing,Software

Reference49 articles.

1. Active appearance models;Cootes;IEEE Trans. Pattern Anal. Mach. Intell.,2001

2. Active shape models-their training and application;Cootes;Comput. Vis. Image Underst.,1995

3. T.F. Cootes, C.J. Taylor, Statistical Models of Appearance for Computer Vision, Tech. rep., Imaging Science and Biomedical Engineering, University of Manchester, 2004.

4. Active appearance models revisited;Matthews;Int. J. Comput. Vis.,2004

5. S. Baker, I. Matthews, Equivalence and efficiency of image alignment algoritms, in: IEEE Conference on Computer Vision and Pattern Recognition, 2001, pp. 1090–1097.

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Landmark Detection Using Convolutional Neural Network: A Review;Lecture Notes in Networks and Systems;2024

2. Sagittal Cervical Spine Landmark Point Detection in X-Ray Using Deep Convolutional Neural Networks;IEEE Access;2022

3. Facial landmark points detection using knowledge distillation-based neural networks;Computer Vision and Image Understanding;2022-01

4. ASMNet: a Lightweight Deep Neural Network for Face Alignment and Pose Estimation;2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW);2021-06

5. Facial Attribute Classification: A Comprehensive Study and a Novel Mid-Level Fusion Classifier;2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems (BTAS);2019-09