Guanyao Wu

According to our database1, Guanyao Wu authored at least 12 papers between 2022 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
CoCoNet: Coupled Contrastive Learning Network with Multi-level Feature Ensemble for Multi-modality Image Fusion.
Int. J. Comput. Vis., May, 2024

Leveraging a self-adaptive mean teacher model for semi-supervised multi-exposure image fusion.
Inf. Fusion, 2024

Where Elegance Meets Precision: Towards a Compact, Automatic, and Flexible Framework for Multi-modality Image Fusion and Applications.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Segmentation-Driven Infrared and Visible Image Fusion Via Transformer-Enhanced Architecture Searching.
Proceedings of the IEEE International Conference on Acoustics, 2024

Hybrid-Supervised Dual-Search: Leveraging Automatic Learning for Loss-Free Multi-Exposure Image Fusion.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
A unified image fusion framework with flexible bilevel paradigm integration.
Vis. Comput., October, 2023

HoLoCo: Holistic and local contrastive learning network for multi-exposure image fusion.
Inf. Fusion, July, 2023

Embracing Compact and Robust Architectures for Multi-Exposure Image Fusion.
CoRR, 2023

Bi-level Dynamic Learning for Jointly Multi-modality Image Fusion and Beyond.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Learn to Search a Lightweight Architecture for Target-Aware Infrared and Visible Image Fusion.
IEEE Signal Process. Lett., 2022

Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022


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