KEPLER: Keypoint and Pose Estimation of Unconstrained Faces by Learning Efficient H-CNN Regressors-Reference-Cited by-同舟云学术

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KEPLER: Keypoint and Pose Estimation of Unconstrained Faces by Learning Efficient H-CNN Regressors

Published:2017-05 Issue: Volume: Page:
ISSN:
Container-title:2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017)
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Author:

Kumar Amit,Alavi Azadeh,Chellappa Rama

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7959734/7961704/07961750.pdf?arnumber=7961750

Cited by 102 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

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2. FIN: A Deep Multi-task Model for Face Information Detection;2023 International Conference on Digital Image Computing: Techniques and Applications (DICTA);2023-11-28

3. Cascaded Iterative Transformer for Jointly Predicting Facial Landmark, Occlusion Probability and Head Pose;International Journal of Computer Vision;2023-11-06

4. LARNeXt: End-to-End Lie Algebra Residual Network for Face Recognition;IEEE Transactions on Pattern Analysis and Machine Intelligence;2023-10

5. Multiple Teacher Knowledge Distillation for Head Pose Estimation Without Keypoints;SN Computer Science;2023-09-29

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