Tianyi Liang

Orcid: 0000-0003-2508-6288

Affiliations:
  • Inspur Group Company Ltd., Shandong, China
  • National University of Defense Technology, College of Computer, Changsha, China (PhD 2022)


According to our database1, Tianyi Liang authored at least 13 papers between 2020 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Compressing the Multiobject Tracking Model via Knowledge Distillation.
IEEE Trans. Comput. Soc. Syst., April, 2024

SBM: Smoothness-Based Minimization for Domain Generalization.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Self-aware circular response-guided attention for robust siamese tracking.
Appl. Intell., June, 2023

Boosting unsupervised domain adaptation: A Fourier approach.
Knowl. Based Syst., March, 2023

Domain-specific feature recalibration and alignment for multi-source unsupervised domain adaptation.
IET Comput. Vis., February, 2023

A Closer Look at the Joint Training of Object Detection and Re-Identification in Multi-Object Tracking.
IEEE Trans. Image Process., 2023

2022
Implicit Feature Alignment For Knowledge Distillation.
Proceedings of the 34th IEEE International Conference on Tools with Artificial Intelligence, 2022

Frustratingly Easy Knowledge Distillation via Attentive Similarity Matching.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

Logit Distillation via Student Diversity.
Proceedings of the Neural Information Processing - 29th International Conference, 2022

2021
A generic MOT boosting framework by combining cues from SOT, tracklet and re-identification.
Knowl. Inf. Syst., 2021

Enhancing the association in multi-object tracking via neighbor graph.
Int. J. Intell. Syst., 2021

InterBN: Channel Fusion for Adversarial Unsupervised Domain Adaptation.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

2020
Enhancing the Association in Multi-Object Tracking via Neighbor Graph.
CoRR, 2020


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