Using Synthetic Data to Improve Facial Expression Analysis with 3D Convolutional Networks-Reference-Cited by-同舟云学术

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Using Synthetic Data to Improve Facial Expression Analysis with 3D Convolutional Networks

Published:2017-10 Issue: Volume: Page:
ISSN:
Container-title:2017 IEEE International Conference on Computer Vision Workshops (ICCVW)
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Author:

Abbasnejad Iman,Sridharan Sridha,Nguyen Dung,Denman Simon,Fookes Clinton,Lucey Simon

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8234943/8265191/08265399.pdf?arnumber=8265399

Cited by 49 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. Qualitative data augmentation for performance prediction in VLSI circuits;Integration;2024-07

2. Training Against Disguises: Addressing and Mitigating Bias in Facial Emotion Recognition with Synthetic Data;2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG);2024-05-27

3. Enhancing ML model accuracy for Digital VLSI circuits using diffusion models: A study on synthetic data generation;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19

4. Cross-Domain Facial Expression Recognition by Combining Transfer Learning and Face-Cycle Generative Adversarial Network;Multimedia Tools and Applications;2024-03-11

5. LSTPNet: Long short-term perception network for dynamic facial expression recognition in the wild;Image and Vision Computing;2024-02

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