1k citations · 2.2k across the 80 of their papers we have counts for
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Practical exposure correction via compensation
Long Ma, Nan An, Jinyuan Liu +4
In computer vision, correcting the exposure level is a fundamental task for enhancing the visual quality of observations with inappropriate lightness. However, existing methodologi…
Breaking Free from Fusion Rule: A Fully Semantic-driven Infrared and Visible Image Fusion
Yuhui Wu, Zhu Liu, Jinyuan Liu +2
Infrared and visible image fusion plays a vital role in the field of computer vision. Previous approaches make efforts to design various fusion rules in the loss functions. However…
Semantic-aware Texture-Structure Feature Collaboration for Underwater Image Enhancement
Di Wang, Long Ma, Risheng Liu +1
Underwater image enhancement has become an attractive topic as a significant technology in marine engineering and aquatic robotics. However, the limited number of datasets and impe…
CoCoNet: Coupled Contrastive Learning Network with Multi-level Feature Ensemble for Multi-modality Image Fusion
Jinyuan Liu, Runjia Lin, Guanyao Wu +3
Infrared and visible image fusion targets to provide an informative image by combining complementary information from different sensors. Existing learning-based fusion approaches a…
Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training
Risheng Liu, Xuan Liu, Shangzhi Zeng +2
Recently, Optimization-Derived Learning (ODL) has attracted attention from learning and vision areas, which designs learning models from the perspective of optimization. However, p…
Unsupervised Misaligned Infrared and Visible Image Fusion via Cross-Modality Image Generation and Registration
Di Wang, Jinyuan Liu, Xin Fan +1
Recent learning-based image fusion methods have marked numerous progress in pre-registered multi-modality data, but suffered serious ghosts dealing with misaligned multi-modality d…
Revisiting GANs by Best-Response Constraint: Perspective, Methodology, and Application
Risheng Liu, Jiaxin Gao, Xuan Liu +1
In past years, the minimax type single-level optimization formulation and its variations have been widely utilized to address Generative Adversarial Networks (GANs). Unfortunately,…
Towards Extremely Fast Bilevel Optimization with Self-governed Convergence Guarantees
Risheng Liu, Xuan Liu, Wei Yao +2
Gradient methods have become mainstream techniques for Bi-Level Optimization (BLO) in learning and vision fields. The validity of existing works heavily relies on solving a series…
Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection
Jinyuan Liu, Xin Fan, Zhanbo Huang +4
This study addresses the issue of fusing infrared and visible images that appear differently for object detection. Aiming at generating an image of high visual quality, previous ap…
Automated Learning for Deformable Medical Image Registration by Jointly Optimizing Network Architectures and Objective Functions
Xin Fan, Zi Li, Ziyang Li +4
Deformable image registration plays a critical role in various tasks of medical image analysis. A successful registration algorithm, either derived from conventional energy optimiz…