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Works176 from public data
- Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement2,440
A novel method, Zero-Reference Deep Curve Estimation (Zero-DCE), which formulates light enhancement as a task of image-specific curve estimation with a deep network and shows that it generalizes well to diverse lighting conditions.
- An Underwater Image Enhancement Benchmark Dataset and Beyond2,368
This paper constructs an Underwater Image Enhancement Benchmark (UIEB) including 950 real-world underwater images, 890 of which have the corresponding reference images and proposes an underwater image enhancement network (called Water-Net) trained on this benchmark as a baseline, which indicates the generalization of the proposed UIEB for training Convolutional Neural Networks (CNNs).
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- Global Context-Aware Progressive Aggregation Network for Salient Object Detection504
This work proposes a novel network named GCPANet to effectively integrate low-level appearance features, high-level semantic features, and global context features through some progressive context-aware Feature Interweaved Aggregation modules and generate the saliency map in a supervised way.
- Review of Visual Saliency Detection With Comprehensive Information419
Different types of saliency detection algorithms are reviewed, the important issues of the existing methods are summarized, the existent problems and future works are discussed, and the experimental analysis and discussion are conducted to provide a holistic overview of differentSaliency detection methods.
- PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN With Dual-Discriminators350
This paper proposes a physical model-guided GAN model for UIE, referred to as PUGAN, and designs the Dual-Discriminators for the style-content adversarial constraint, promoting the authenticity and visual aesthetics of the results.
- Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images350
An end-to-end Dense Attention Fluid Network (DAFNet) for SOD in optical RSIs that significantly outperforms the existing state-of-the-art SOD competitors is proposed and a new and challenging optical RSI dataset is constructed that contains 2,000 images with pixel-wise saliency annotations.
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- Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion235
A measure to evaluate the reliability of depth map, and use it to reduce the influence of poor depth map on saliency detection, and two saliency maps are integrated into a final saliency map through weighted-sum method according to their importance.
- CIR-Net: Cross-Modality Interaction and Refinement for RGB-D Salient Object Detection229
A convolutional neural network (CNN) model, named CIR-Net, based on the novel cross-modality interaction and refinement is presented, which outperforms the state-of-the-art saliency detectors both qualitatively and quantitatively.
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- A hybrid method for underwater image correction220
Subjective and objective performance evaluations demonstrate that the proposed method significantly improves both color and visibility of degraded underwater images, and is comparable to and even outperforms several state-of-the-art methods.
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- Frequency Perception Network for Camouflaged Object Detection158
This work proposes a novel learnable and separable frequency perception mechanism driven by the semantic hierarchy in the frequency domain that achieves competitive performance in three popular benchmark datasets both qualitatively and quantitatively.
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- RGB-D Salient Object Detection with Cross-Modality Modulation and Selection149
A cross-modality feature modulation module to enhance feature representations by taking the depth features as prior, which models the complementary relations of RGB-D data and an adaptive feature selection module to select saliency-related features and suppress the inferior ones.
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- Cross-modality Discrepant Interaction Network for RGB-D Salient Object Detection142
A novel Cross-modality Discrepant Interaction Network (CDINet) for RGB-D SOD is proposed, which differentially models the dependence of two modalities according to the feature representations of different layers, and outperforms state-of-the-art methods both quantitatively and qualitatively.
- Perceptual hashing for image authentication: A survey139
In this article, the general structure and classifications of image hashing based tamper detection techniques with their properties are exploited and the evaluation datasets and different performance metrics are discussed.
- Does Thermal Really Always Matter for RGB-T Salient Object Detection?136
A global illumination estimation module to predict the global illuminance score of the image, so as to regulate the role played by the two modalities, and proposes a network named TNet to solve the RGB-T SOD task.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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