1 citations · 1 across the 3 of their papers we have counts for
6 papers
Enhancing Infrared Vision: Progressive Prompt Fusion Network and Benchmark
Jinyuan Liu, Zihang Chen, Zhu Liu +4
We engage in the relatively underexplored task named thermal infrared image enhancement. Existing infrared image enhancement methods primarily focus on tackling individual degradat…
DCEvo: Discriminative Cross-Dimensional Evolutionary Learning for Infrared and Visible Image Fusion
Jinyuan Liu, Bowei Zhang, Qingyun Mei +6
Infrared and visible image fusion integrates information from distinct spectral bands to enhance image quality by leveraging the strengths and mitigating the limitations of each mo…
DifIISR: A Diffusion Model with Gradient Guidance for Infrared Image Super-Resolution
Xingyuan Li, Zirui Wang, Yang Zou +5
Infrared imaging is essential for autonomous driving and robotic operations as a supportive modality due to its reliable performance in challenging environments. Despite its popula…
DEAL: Data-Efficient Adversarial Learning for High-Quality Infrared Imaging
Zhu Liu, Zijun Wang, Jinyuan Liu +3
Thermal imaging is often compromised by dynamic, complex degradations caused by hardware limitations and unpredictable environmental factors. The scarcity of high-quality infrared…
HUPE: Heuristic Underwater Perceptual Enhancement with Semantic Collaborative Learning
Zengxi Zhang, Zhiying Jiang, Long Ma +3
Underwater images are often affected by light refraction and absorption, reducing visibility and interfering with subsequent applications. Existing underwater image enhancement met…
Contourlet Refinement Gate Framework for Thermal Spectrum Distribution Regularized Infrared Image Super-Resolution
Yang Zou, Zhixin Chen, Zhipeng Zhang +5
Image super-resolution (SR) is a classical yet still active low-level vision problem that aims to reconstruct high-resolution (HR) images from their low-resolution (LR) counterpart…