Chang Liu

Affiliations:
  • Nanyang Technological University (NTU), Singapore


According to our database1, Chang Liu authored at least 14 papers between 2021 and 2024.

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

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
PrimitiveNet: decomposing the global constraints for referring segmentation.
Vis. Intell., 2024

LSVOS Challenge Report: Large-scale Complex and Long Video Object Segmentation.
CoRR, 2024

PVUW 2024 Challenge on Complex Video Understanding: Methods and Results.
CoRR, 2024

Referring Image Editing: Object-Level Image Editing via Referring Expressions.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
VLT: Vision-Language Transformer and Query Generation for Referring Segmentation.
IEEE Trans. Pattern Anal. Mach. Intell., June, 2023

Instance-Specific Feature Propagation for Referring Segmentation.
IEEE Trans. Multim., 2023

Multi-Modal Mutual Attention and Iterative Interaction for Referring Image Segmentation.
IEEE Trans. Image Process., 2023

GREC: Generalized Referring Expression Comprehension.
CoRR, 2023

MOSE: A New Dataset for Video Object Segmentation in Complex Scenes.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

GRES: Generalized Referring Expression Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Deep Interactive Image Matting With Feature Propagation.
IEEE Trans. Image Process., 2022

2021
Towards Enhancing Fine-grained Details for Image Matting.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Vision-Language Transformer and Query Generation for Referring Segmentation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021


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