Chao Huang

Orcid: 0000-0003-1490-2171

Affiliations:
  • Harbin Institute of Technology, Shenzhen, China
  • Ningbo University, Faculty of Information Science and Engineering, China (former)


According to our database1, Chao Huang authored at least 25 papers between 2018 and 2024.

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

Timeline

Legend:

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Online presence:

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Bibliography

2024
Video-Based Fall Detection Using Human Pose and Constrained Generative Adversarial Network.
IEEE Trans. Circuits Syst. Video Technol., April, 2024

HACDR-Net: Heterogeneous-Aware Convolutional Network for Diabetic Retinopathy Multi-Lesion Segmentation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Attention-Induced Embedding Imputation for Incomplete Multi-View Partial Multi-Label Classification.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Self-Supervised Attentive Generative Adversarial Networks for Video Anomaly Detection.
IEEE Trans. Neural Networks Learn. Syst., November, 2023

Class-guided human motion prediction via multi-spatial-temporal supervision.
Neural Comput. Appl., May, 2023

Localized Sparse Incomplete Multi-View Clustering.
IEEE Trans. Multim., 2023

Robust fall detection in video surveillance based on weakly supervised learning.
Neural Networks, 2023

Information Recovery-Driven Deep Incomplete Multi-view Clustering Network.
CoRR, 2023

Masked Two-channel Decoupling Framework for Incomplete Multi-view Weak Multi-label Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Localized and Balanced Efficient Incomplete Multi-view Clustering.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

Highly Confident Local Structure Based Consensus Graph Learning for Incomplete Multi-view Clustering.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

CIGAR: Cross-Modality Graph Reasoning for Domain Adaptive Object Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Unsupervised Decomposition and Correction Network for Low-Light Image Enhancement.
IEEE Trans. Intell. Transp. Syst., 2022

Abnormal Event Detection Using Deep Contrastive Learning for Intelligent Video Surveillance System.
IEEE Trans. Ind. Informatics, 2022

Self-Supervision-Augmented Deep Autoencoder for Unsupervised Visual Anomaly Detection.
IEEE Trans. Cybern., 2022

Weakly Supervised Video Anomaly Detection via Transformer-Enabled Temporal Relation Learning.
IEEE Signal Process. Lett., 2022

Pixel-Level Anomaly Detection via Uncertainty-aware Prototypical Transformer.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Hierarchical Graph Embedded Pose Regularity Learning via Spatio-Temporal Transformer for Abnormal Behavior Detection.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Deep Object Detection with Example Attribute Based Prediction Modulation.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Online Learning-Based Multi-Stage Complexity Control for Live Video Coding.
IEEE Trans. Image Process., 2021

Inter-layer correlation-based adaptive bit allocation for enhancement layer in scalable high efficiency video coding.
Signal Process. Image Commun., 2021

2019
Multiple classifier-based fast coding unit partition for intra coding in future video coding.
Signal Process. Image Commun., 2019

Encoding Complexity Control for Live Video Applications: An Interpretable Machine Learning Approach.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2019

2018
Efficient CU and PU Decision Based on Neural Network and Gray Level Co-Occurrence Matrix for Intra Prediction of Screen Content Coding.
IEEE Access, 2018


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