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Existing low-light image enhancement (LLIE) and joint LLIE and deblurring (LLIE-deblur) models have made strides in addressing predefined degradations, yet they are often constrained by dynamically coupled degradations. To address these…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Rui Xu , Yuzhen Niu , Yuezhou Li , Huangbiao Xu , Wenxi Liu , Yuzhong Chen

Low-light image enhancement (LLIE) has traditionally been formulated as a deterministic mapping. However, this paradigm often struggles to account for the ill-posed nature of the task, where unknown ambient conditions and sensor parameters…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Hongru Han , Tingrui Guo , Liming Zhang , Yan Su , Qiwen Xu , Zhuohua Ye

Low-light image enhancement remains a challenging task, particularly in preserving object edge continuity and fine structural details under extreme illumination degradation. In this paper, we propose a novel model, DRWKV (Detailed…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Xuecheng Bai , Yuxiang Wang , Boyu Hu , Qinyuan Jie , Chuanzhi Xu , Kechen Li , Hongru Xiao , Vera Chung

Low-light video enhancement (LLVE) is an important yet challenging task with many applications such as photographing and autonomous driving. Unlike single image low-light enhancement, most LLVE methods utilize temporal information from…

Computer Vision and Pattern Recognition · Computer Science 2022-08-24 Lin Liu , Junfeng An , Jianzhuang Liu , Shanxin Yuan , Xiangyu Chen , Wengang Zhou , Houqiang Li , Yanfeng Wang , Qi Tian

Event camera has recently received much attention for low-light image enhancement (LIE) thanks to their distinct advantages, such as high dynamic range. However, current research is prohibitively restricted by the lack of large-scale,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Guoqiang Liang , Kanghao Chen , Hangyu Li , Yunfan Lu , Lin Wang

Low-light image enhancement (LLIE) aims to improve the visibility of images captured in poorly lit environments. Prevalent event-based solutions primarily utilize events triggered by motion, i.e., ''motion events'' to strengthen only the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Lei Sun , Yuhan Bao , Jiajun Zhai , Jingyun Liang , Yulun Zhang , Kaiwei Wang , Danda Pani Paudel , Luc Van Gool

The event camera, benefiting from its high dynamic range and low latency, provides performance gain for low-light image enhancement. Unlike frame-based cameras, it records intensity changes with extremely high temporal resolution, capturing…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Chunyan She , Fujun Han , Chengyu Fang , Shukai Duan , Lidan Wang

Event cameras offer significant advantages for low-light video enhancement, primarily due to their high dynamic range. Current research, however, is severely limited by the absence of large-scale, real-world, and spatio-temporally aligned…

Computer Vision and Pattern Recognition · Computer Science 2024-08-30 Kanghao Chen , Guoqiang Liang , Hangyu Li , Yunfan Lu , Lin Wang

Event cameras, with their high dynamic range, show great promise for Low-light Image Enhancement (LLIE). Existing works primarily focus on designing effective modal fusion strategies. However, a key challenge is the dual degradation from…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Zishu Yao , Xiang-Xiang Su , Shengning Zhou , Guang-Yong Chen , Guodong Fan , Xing Chen

Under extreme low-light conditions, frame-based cameras suffer from severe detail loss due to limited dynamic range. Recent studies have introduced event cameras for event-guided low-light image enhancement. However, existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Zhanwen Liu , Huanna Song , Yang Wang , Nan Yang , Weiping Ding , Yisheng An

In low-light conditions, capturing videos with frame-based cameras often requires long exposure times, resulting in motion blur and reduced visibility. While frame-based motion deblurring and low-light enhancement have been studied, they…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Taewoo Kim , Jaeseok Jeong , Hoonhee Cho , Yuhwan Jeong , Kuk-Jin Yoon

Overexposure frequently occurs in practical scenarios, causing the loss of critical visual information. However, existing infrared and visible fusion methods still exhibit unsatisfactory performance in highly bright regions. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Zhiwei Wang , Yayu Zheng , Defeng He , Li Zhao , Xiaoqin Zhang , Yuxing Li , Edmund Y. Lam

Low-Light Video Enhancement (LLVE) seeks to restore dynamic or static scenes plagued by severe invisibility and noise. In this paper, we present an innovative video decomposition strategy that incorporates view-independent and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Xiaogang Xu , Kun Zhou , Tao Hu , Jiafei Wu , Ruixing Wang , Hao Peng , Bei Yu

In photogrammetry, accurately fusing infrared (IR) and visible (VIS) spectra while preserving the geometric fidelity of visible features and incorporating thermal radiation is a significant challenge, particularly under extreme conditions.…

Computer Vision and Pattern Recognition · Computer Science 2026-01-14 Jing Tao , Yonghong Zong , Banglei Guan , Pengju Sun , Taihang Lei , Yang Shanga , Qifeng Yu

Low-Light Video Enhancement (LLVE) seeks to restore dynamic or static scenes plagued by severe invisibility and noise. In this paper, we present an innovative video decomposition strategy that incorporates view-independent and…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Xiaogang Xu , Kun Zhou , Tao Hu , Jiafei Wu , Ruixing Wang , Hao Peng , Bei Yu

Event-based low-light image enhancement (LIE) methods mainly focus on incorporating high dynamic range (HDR) information from events while overlooking the essential global illumination in images and the inherent noise sensitivity of event…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Senyan Xu , Zhijing Sun , Kean Liu , Xin Lu , Ruixuan Jiang , Mingyang Huang , Xueyang Fu , Zheng-Jun Zha

In the current era of mobile internet, Lightweight Low-Light Image Enhancement (L3IE) is critical for mobile devices, which faces a persistent trade-off between visual quality and model compactness. While recent methods employ disentangling…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Hailong Yan , Shice Liu , Xiangtao Zhang , Lujian Yao , Fengxiang Yang , Jinwei Chen , Bo Li

Event-based semantic segmentation explores the potential of event cameras, which offer high dynamic range and fine temporal resolution, to achieve robust scene understanding in challenging environments. Despite these advantages, the task…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Zhijiang Li , Haoran He

High-resolution remote sensing analysis faces challenges in global context modeling due to scene complexity and scale diversity. While CNNs excel at local feature extraction via parameter sharing, their fixed receptive fields fundamentally…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Chunshan Li , Rong Wang , Xiaofei Yang , Dianhui Chu

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 modality. Existing approaches typically treat image fusion and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Jinyuan Liu , Bowei Zhang , Qingyun Mei , Xingyuan Li , Yang Zou , Zhiying Jiang , Long Ma , Risheng Liu , Xin Fan
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