Pengwei Liang

Orcid: 0000-0003-0173-1385

According to our database1, Pengwei Liang authored at least 16 papers between 2019 and 2024.

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

Timeline

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Links

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Bibliography

2024
GAS-AU: an average uncertainty-based general adaptive sampling approach.
Eng. Comput., April, 2024

Decoupling Image Deblurring Into Twofold: A Hierarchical Model for Defocus Deblurring.
IEEE Trans. Computational Imaging, 2024

MaeFuse: Transferring Omni Features with Pretrained Masked Autoencoders for Infrared and Visible Image Fusion via Guided Training.
CoRR, 2024

2023
Learning to remove sandstorm for image enhancement.
Vis. Comput., May, 2023

Image Deblurring by Exploring In-depth Properties of Transformer.
CoRR, 2023

2022
Multi-scale and multi-patch transformer for sandstorm image enhancement.
J. Vis. Commun. Image Represent., 2022

BaMBNet: A Blur-Aware Multi-Branch Network for Dual-Pixel Defocus Deblurring.
IEEE CAA J. Autom. Sinica, 2022

Underwater image enhancement by maximum-likelihood based adaptive color correction and robust scattering removal.
Frontiers Comput. Sci., 2022

Fusion from Decomposition: A Self-Supervised Decomposition Approach for Image Fusion.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
GANMcC: A Generative Adversarial Network With Multiclassification Constraints for Infrared and Visible Image Fusion.
IEEE Trans. Instrum. Meas., 2021

BaMBNet: A Blur-aware Multi-branch Network for Defocus Deblurring.
CoRR, 2021

2020
Pan-GAN: An unsupervised pan-sharpening method for remote sensing image fusion.
Inf. Fusion, 2020

Infrared and visible image fusion via detail preserving adversarial learning.
Inf. Fusion, 2020

2019
Deep transfer learning for military object recognition under small training set condition.
Neural Comput. Appl., 2019

FusionGAN: A generative adversarial network for infrared and visible image fusion.
Inf. Fusion, 2019

Learning a Generative Model for Fusing Infrared and Visible Images via Conditional Generative Adversarial Network with Dual Discriminators.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019


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