Mouxing Yang

Orcid: 0000-0001-8544-6375

According to our database1, Mouxing Yang authored at least 14 papers between 2021 and 2025.

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

Timeline

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Bibliography

2025
Noise-Robust Vision-Language Pre-Training With Positive-Negative Learning.
IEEE Trans. Pattern Anal. Mach. Intell., January, 2025

2024
Robust Object Re-identification with Coupled Noisy Labels.
Int. J. Comput. Vis., July, 2024

Semantic Invariant Multi-View Clustering With Fully Incomplete Information.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2024

Cross-Modal Retrieval With Noisy Correspondence via Consistency Refining and Mining.
IEEE Trans. Image Process., 2024

Test-time Adaptation for Cross-modal Retrieval with Query Shift.
CoRR, 2024

An Empirical Study of Parameter Efficient Fine-tuning on Vision-Language Pre-train Model.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Test-time Adaptation against Multi-modal Reliability Bias.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Decoupled Contrastive Multi-View Clustering with High-Order Random Walks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Robust Multi-View Clustering With Incomplete Information.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Incomplete Multi-view Clustering via Prototype-based Imputation.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Graph Matching with Bi-level Noisy Correspondence.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Twin Contrastive Learning for Online Clustering.
Int. J. Comput. Vis., 2022

Learning with Twin Noisy Labels for Visible-Infrared Person Re-Identification.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Partially View-Aligned Representation Learning With Noise-Robust Contrastive Loss.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021


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