Yingruo Fan

Orcid: 0000-0001-8977-4958

According to our database1, Yingruo Fan authored at least 12 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
BodyFormer: Semantics-guided 3D Body Gesture Synthesis with Transformer.
ACM Trans. Graph., August, 2023

Distilling Region-Wise and Channel-Wise Deep Structural Facial Relationships for FAU (DSR-FAU) Intensity Estimation.
IEEE Trans. Affect. Comput., 2023

2022
Facial Expression Recognition With Deeply-Supervised Attention Network.
IEEE Trans. Affect. Comput., 2022

Joint Audio-Text Model for Expressive Speech-Driven 3D Facial Animation.
Proc. ACM Comput. Graph. Interact. Tech., 2022

FaceFormer: Speech-Driven 3D Facial Animation with Transformers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2020
G2RL: Geometry-Guided Representation Learning for Facial Action Unit Intensity Estimation.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2018
Video-based Emotion Recognition Using Deeply-Supervised Neural Networks.
Proceedings of the 2018 on International Conference on Multimodal Interaction, 2018

Multi-region Ensemble Convolutional Neural Network for Facial Expression Recognition.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Unsupervised Domain Adaptation with Generative Adversarial Networks for Facial Emotion Recognition.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017
The Visual Object Tracking VOT2017 Challenge Results.
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Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

Correlation Filters with Weighted Convolution Responses.
Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017


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