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Adversarially Regularized Low-Light Image Enhancement
The task of low-light image enhancement aims to generate clear images from their poorly visible counterparts taken under low-light conditions. While...
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Low-light DEtection TRansformer (LDETR): object detection in low-light and adverse weather conditions
Object detection has recently gained popularity mainly due to the development of deep learning techniques. However, undesirable noise challenges...
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Low-Light Image Enhancement via Unsupervised Learning
The models based on unsupervised learning methods have achieved prominent achievement in several low-level tasks such as image restoration and...
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Dual-band low-light image enhancement
Most of the existing low-light image enhancement algorithms are designed for one kind of low-light image, which cannot effectively handle the...
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Low-Light Image Enhancement Using Zero-DCE and DCP
In this paper, a new low-light enhancement technique is proposed to enhance the performance of images. This technique is obtained by fusing...
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EAT: epipolar-aware Transformer for low-light light field enhancement
Current low-light light field (LF) enhancement methods are mainly based on the convolutional neural network and have achieved considerable effect....
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LIELFormer: Low-Light Image Enhancement with a Lightweight Transformer
Images captured under low-light conditions often suffer from (partially) poor visibility. One of the challenges of low-light enhancement, in addition...
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Self-supervised Low-Light Image Enhancement via Histogram Equalization Prior
Deep learning-based methods for low-light image enhancement have achieved remarkable success. However, the requirement of enormous paired real data...
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Fusion-Based Low-Light Image Enhancement
Recently, deep learning-based methods have made remarkable progress in low-light image enhancement. In addition to poor contrast, the images captured...
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Luminance domain-guided low-light image enhancement
Images captured under low-light conditions often suffer from low contrast, high noise, and uneven brightness due to nightlight, backlight, and...
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A novel low complexity retinex-based algorithm for enhancing low-light images
Retinex-based algorithms, drawing inspiration from the human visual system biology, have emerged as favored techniques in literature for enhancing...
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STransLOT: splitting-refusion transformer for low-light object tracking
In the field of tracking, more and more trackers are using the great potential of the transformer to form the framework. Most of them use the...
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Low-Light Image Enhancement Under Non-uniform Dark
The low visibility of low-light images due to lack of exposure poses a significant challenge for vision tasks such as image fusion, detection and...
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Lane Detection Method under Low-Light Conditions Combining Feature Aggregation and Light Style Transfer
AbstractDeep learning technology is widely used in lane detection, but applying this technology to conditions such as environmental occlusion and low...
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Improving Person Re-identification Through Low-Light Image Enhancement
Person re-identification (ReID) is a popular area of research in the field of computer vision. Despite the significant advancements achieved in...
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Local Dynamic Filter Network for Low-Light Enhancement and Deblurring
Under specific conditions, capturing clear images that meet human vision requirements is challenging due to limitations in electronic devices and...
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Adaptive Enhancement of Extreme Low-Light Images
Existing methods for enhancing dark images captured in a very low-light environment assume that the intensity level of the optimal output image is...
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Rethinking Zero-DCE for Low-Light Image Enhancement
Zero-Reference Deep Curve Estimation (Zero-DCE) is currently one of the most popular low-light image enhancement methods. Through extensive...
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L \(^2\) DM: A Diffusion Model for Low-Light Image Enhancement
Low-light image enhancement is a challenging yet beneficial task in computer vision that aims to improve the quality of images captured under poor...
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Filter-cluster attention based recursive network for low-light enhancement
The poor quality of images recorded in low-light environments affects their further applications. To improve the visibility of low-light images, we...