Papers Exposure Correction
“Exposure Correction” 태그가 달린 논문 43편 · 필터 해제
Learning to See in the Extremely Dark
Learning-based methods have made promising advances in low-light RAW image enhancement, while their capability to extremely dark scenes where the environmental illuminance drops as low as 0.0001 lux remains to be explore…
DenoisingExposure CorrectionImage EnhancementExposure-slot: Exposure-centric representations learning with Slot-in-Slot Attention for Region-aware Exposure Correction
Image exposure correction enhances images captured under diverse real-world conditions by addressing issues of under- and over-exposure, which can result in the loss of critical details and hinder content recognition. Wh…
Exposure CorrectionImage EnhancementLearning to Harmonize Cross-vendor X-ray Images by Non-linear Image Dynamics Correction
In this paper, we explore how conventional image enhancement can improve model robustness in medical image analysis. By applying commonly used normalization methods to images from various vendors and studying their influ…
Exposure CorrectionImage EnhancementImage HarmonizationMedical Image Analysis+1Discovering an Image-Adaptive Coordinate System for Photography Processing
Curve & Lookup Table (LUT) based methods directly map a pixel to the target output, making them highly efficient tools for real-time photography processing. However, due to extreme memory complexity to learn full RGB spa…
Exposure CorrectionPhoto RetouchingHipyrNet: Hypernet-Guided Feature Pyramid network for mixed-exposure correction
Recent advancements in image translation for enhancing mixed-exposure images have demonstrated the transformative potential of deep learning algorithms. However, addressing extreme exposure variations in images remains a…
Exposure CorrectionImage EnhancementTranslationLITA-GS: Illumination-Agnostic Novel View Synthesis via Reference-Free 3D Gaussian Splatting and Physical Priors
Directly employing 3D Gaussian Splatting (3DGS) on images with adverse illumination conditions exhibits considerable difficulty in achieving high-quality normally-exposed representation due to: (1) The limited Struct…
3DGSDenoisingExposure CorrectionNeRF+2Learning Adaptive Lighting via Channel-Aware Guidance
Learning lighting adaptation is a crucial step in achieving good visual perception and supporting downstream vision tasks. Current research often addresses individual light-related challenges, such as high dynamic range …
Exposure CorrectionImage RetouchingLuminance Component Analysis for Exposure Correction
Exposure correction methods aim to adjust the luminance while maintaining other luminance-unrelated information. However, current exposure correction methods have difficulty in fully separating luminance-related and lumi…
Exposure CorrectionSSIMOSMamba: Omnidirectional Spectral Mamba with Dual-Domain Prior Generator for Exposure Correction
Exposure correction is a fundamental problem in computer vision and image processing. Recently, frequency domain-based methods have achieved impressive improvement, yet they still struggle with complex real-world scenari…
Exposure CorrectionMambaState Space ModelsECMamba: Consolidating Selective State Space Model with Retinex Guidance for Efficient Multiple Exposure Correction
Exposure Correction (EC) aims to recover proper exposure conditions for images captured under over-exposure or under-exposure scenarios. While existing deep learning models have shown promising results, few have fully em…
Exposure CorrectionMambaRetinex-RAWMamba: Bridging Demosaicing and Denoising for Low-Light RAW Image Enhancement
Low-light image enhancement, particularly in cross-domain tasks such as mapping from the raw domain to the sRGB domain, remains a significant challenge. Many deep learning-based methods have been developed to address thi…
DemosaickingDenoisingExposure CorrectionImage Enhancement+2EndoUIC: Promptable Diffusion Transformer for Unified Illumination Correction in Capsule Endoscopy
Wireless Capsule Endoscopy (WCE) is highly valued for its non-invasive and painless approach, though its effectiveness is compromised by uneven illumination from hardware constraints and complex internal dynamics, leadin…
Exposure CorrectionImage EnhancementNavigateRepresentation LearningColor Shift Estimation-and-Correction for Image Enhancement
Images captured under sub-optimal illumination conditions may contain both over- and under-exposures. Current approaches mainly focus on adjusting image brightness, which may exacerbate the color tone distortion in under…
Exposure CorrectionImage EnhancementLow-Light Image EnhancementLight-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language Guidance
Recently, User-Generated Content (UGC) videos have gained popularity in our daily lives. However, UGC videos often suffer from poor exposure due to the limitations of photographic equipment and techniques. Therefore, Vid…
Exposure CorrectionVideo EnhancementVideo Quality AssessmentVisual Question Answering (VQA)Deep unfolding Network for Hyperspectral Image Super-Resolution with Automatic Exposure Correction
In recent years, the fusion of high spatial resolution multispectral image (HR-MSI) and low spatial resolution hyperspectral image (LR-HSI) has been recognized as an effective method for HSI super-resolution (HSI-SR). Ho…
Exposure CorrectionHyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionRegion-Aware Exposure Consistency Network for Mixed Exposure Correction
Exposure correction aims to enhance images suffering from improper exposure to achieve satisfactory visual effects. Despite recent progress, existing methods generally mitigate either overexposure or underexposure in inp…
Exposure CorrectionLearning Exposure Correction in Dynamic Scenes
Exposure correction aims to enhance visual data suffering from improper exposures, which can greatly improve satisfactory visual effects. However, previous methods mainly focus on the image modality, and the video counte…
Exposure CorrectionVideo EnhancementFD-Vision Mamba for Endoscopic Exposure Correction
In endoscopic imaging, the recorded images are prone to exposure abnormalities, so maintaining high-quality images is important to assist healthcare professionals in performing decision-making. To overcome this issue, We…
Decision MakingExposure CorrectionMambaReal-Time Exposure Correction via Collaborative Transformations and Adaptive Sampling
Most of the previous exposure correction methods learn dense pixel-wise transformations to achieve promising results but consume huge computational resources. Recently Learnable 3D lookup tables (3D LUTs) have demons…
Exposure CorrectionImage Enhancement4K-Resolution Photo Exposure Correction at 125 FPS with ~8K Parameters
The illumination of improperly exposed photographs has been widely corrected using deep convolutional neural networks or Transformers. Despite with promising performance, these methods usually suffer from large parameter…
4k8kExposure CorrectionGPU