activity
20172021
most citedRetinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement

60 citations · 107 across the 7 of their papers we have counts for

collaborators

15 papers

cs.CV20222 cited

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…

cs.LG20223 cited

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,…

cs.CV202231 cited

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…

cs.CV20216 cited

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…

cs.CV202060 cited

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…

eess.IV20191 cited

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…