254 citations · 896 across the 31 of their papers we have counts for
31 papers
Learning Heavily-Degraded Prior for Underwater Object Detection
Chenping Fu, Xin Fan, Jiewen Xiao +3
Underwater object detection suffers from low detection performance because the distance and wavelength dependent imaging process yield evident image quality degradations such as ha…
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…
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…
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,…
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…
Learning Deep Context-Sensitive Decomposition for Low-Light Image Enhancement
Long Ma, Risheng Liu, Jiaao Zhang +2
Enhancing the quality of low-light images plays a very important role in many image processing and multimedia applications. In recent years, a variety of deep learning techniques h…
Learning with Nested Scene Modeling and Cooperative Architecture Search for Low-Light Vision
Risheng Liu, Long Ma, Tengyu Ma +2
Images captured from low-light scenes often suffer from severe degradations, including low visibility, color cast and intensive noises, etc. These factors not only affect image qua…
Triple-level Model Inferred Collaborative Network Architecture for Video Deraining
Pan Mu, Zhu Liu, Yaohua Liu +2
Video deraining is an important issue for outdoor vision systems and has been investigated extensively. However, designing optimal architectures by the aggregating model formation…
An Underwater Image Semantic Segmentation Method Focusing on Boundaries and a Real Underwater Scene Semantic Segmentation Dataset
Zhiwei Ma, Haojie Li, Zhihui Wang +5
With the development of underwater object grabbing technology, underwater object recognition and segmentation of high accuracy has become a challenge. The existing underwater objec…
A Dataset And Benchmark Of Underwater Object Detection For Robot Picking
Chongwei Liu, Haojie Li, Shuchang Wang +4
Underwater object detection for robot picking has attracted a lot of interest. However, it is still an unsolved problem due to several challenges. We take steps towards making it m…
Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement
Risheng Liu, Long Ma, Jiaao Zhang +2
Low-light image enhancement plays very important roles in low-level vision field. Recent works have built a large variety of deep learning models to address this task. However, the…
Optimization-Inspired Learning with Architecture Augmentations and Control Mechanisms for Low-Level Vision
Risheng Liu, Zhu Liu, Pan Mu +2
In recent years, there has been a growing interest in combining learnable modules with numerical optimization to solve low-level vision tasks. However, most existing approaches foc…
Learning Deformable Image Registration from Optimization: Perspective, Modules, Bilevel Training and Beyond
Risheng Liu, Zi Li, Xin Fan +3
Conventional deformable registration methods aim at solving an optimization model carefully designed on image pairs and their computational costs are exceptionally high. In contras…
Converged Deep Framework Assembling Principled Modules for CS-MRI
Risheng Liu, Yuxi Zhang, Shichao Cheng +2
Compressed Sensing Magnetic Resonance Imaging (CS-MRI) significantly accelerates MR data acquisition at a sampling rate much lower than the Nyquist criterion. A major challenge for…
Investigating Task-driven Latent Feasibility for Nonconvex Image Modeling
Risheng Liu, Pan Mu, Jian Chen +2
Properly modeling latent image distributions plays an important role in a variety of image-related vision problems. Most exiting approaches aim to formulate this problem as optimiz…
Underexposed Image Correction via Hybrid Priors Navigated Deep Propagation
Risheng Liu, Long Ma, Yuxi Zhang +2
Enhancing visual qualities for underexposed images is an extensively concerned task that plays important roles in various areas of multimedia and computer vision. Most existing met…
Real-world Underwater Enhancement: Challenges, Benchmarks, and Solutions
Risheng Liu, Xin Fan, Ming Zhu +2
Underwater image enhancement is such an important low-level vision task with many applications that numerous algorithms have been proposed in recent years. These algorithms develop…
High accuracy analysis of a nonconforming discrete Stokes complex over rectangular meshes
Xinchen Zhou, Zhaoliang Meng, Xin Fan +1
This work is devoted to the high accuracy analysis of a discrete Stokes complex over rectangular meshes with a simple structure. The 0-form in the complex is a non nonconform…
Two 11-node nonconforming triangular prism elements for 3D elliptic problems
Xinchen Zhou, Zhaoliang Meng, Xin Fan +1
This work introduces two 11-node triangular prism elements for 3D elliptic problems. The degrees of freedom (DoFs) of both elements are at the vertices and face centroids of a pris…
A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI
Risheng Liu, Yuxi Zhang, Shichao Cheng +2
Magnetic Resonance Imaging (MRI) is one of the most dynamic and safe imaging techniques available for clinical applications. However, the rather slow speed of MRI acquisitions limi…
A nodal type polynomial finite element exact sequence over quadrilaterals
Xinchen Zhou, Zhaoliang Meng, Xin Fan +1
This work proposes two nodal type nonconforming finite elements over convex quadrilaterals, which are parts of a finite element exact sequence. Both elements are of 12 degrees of f…