Qi Liang

Orcid: 0000-0001-5598-6012

Affiliations:
  • Tianjin University, School of Electrical and Information Engineering, China


According to our database1, Qi Liang authored at least 15 papers between 2019 and 2023.

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

Timeline

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Bibliography

2023
Principal views selection based on growing graph convolution network for multi-view 3D model recognition.
Appl. Intell., March, 2023

Unsupervised Cross-Media Graph Convolutional Network for 2D Image-Based 3D Model Retrieval.
IEEE Trans. Multim., 2023

2022
LD-GAN: Learning perturbations for adversarial defense based on GAN structure.
Signal Process. Image Commun., 2022

PAGN: perturbation adaption generation network for point cloud adversarial defense.
Multim. Syst., 2022

JFLN: Joint Feature Learning Network for 2D sketch based 3D shape retrieval.
J. Vis. Commun. Image Represent., 2022

LP-GAN: Learning perturbations based on generative adversarial networks for point cloud adversarial attacks.
Image Vis. Comput., 2022

LIMAN: Local Information-Based Multiattention Network for 3D Shape Recognition.
IEEE Multim., 2022

2021
MMFN: Multimodal Information Fusion Networks for 3D Model Classification and Retrieval.
ACM Trans. Multim. Comput. Commun. Appl., 2021

MHFP: Multi-view based hierarchical fusion pooling method for 3D shape recognition.
Pattern Recognit. Lett., 2021

Exposing DeepFake Videos Using Attention Based Convolutional LSTM Network.
Neural Process. Lett., 2021

3D shape recognition based on multi-modal information fusion.
Multim. Tools Appl., 2021

2020
Two-Stream Network Based on Visual Saliency Sharing for 3D Model Recognition.
IEEE Access, 2020

MVCLN: Multi-View Convolutional LSTM Network for Cross-Media 3D Shape Recognition.
IEEE Access, 2020

2019
Panorama based on multi-channel-attention CNN for 3D model recognition.
Multim. Syst., 2019

MMJN: Multi-Modal Joint Networks for 3D Shape Recognition.
Proceedings of the 27th ACM International Conference on Multimedia, 2019


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