Papers Image Deblurring
“Image Deblurring” 태그가 달린 논문 434편 · 필터 해제
GS-RealBlur: A Flexible Data Acquisition Framework for Real-World Image Deblurring
High-quality, large-scale paired data is essential for training learning-based image deblurring models. However, synthetic blurry images generally lack realism, while real-world captured images require complex and inflex…
Image DeblurringDICT: Data Injection and Contrastive Trajectory Refinement for Conditional Image Generation with Diffusion Models
Diffusion models have become a dominant paradigm for conditional image generation, yet existing approaches generally follow two directions: task-specific designs that can improve performance but limit generalization, and…
Conditional Image GenerationImage Super-ResolutionImage DeblurringStyle TransferLeveraging Phase Information to Boost Unrolled Network Learning for Image Deblurring
While most image deblurring techniques directly restore the spatial image variable, we propose an amplitude and phase decomposition recognizing the importance of accurate phase estimation in recovering sharp image detail…
Image DeblurringCogSENet: Blind Image Deblurring with Blur-Conditioned Semantic Routing and Explicit Frequency Fusion
Blind image deblurring demands the recovery of high-fidelity details and coherent structures from complex, unknown degradations. Current blind image deblurring methods struggle with real-world, spatially varying degradat…
Image DeblurringFSM-Net: An Efficient Frequency-Spatial Network for Real-World Deblurring
Real-world image deblurring demands both high-fidelity restoration and computational efficiency, a balance existing methods often struggle to achieve. In this paper, we propose FSM-Net (Frequency-Spatial Multi-branch Net…
Computational EfficiencyImage RestorationImage DeblurringStop Denoising Your Blurs
In recent times, diffusion models have achieved remarkable performance in image restoration tasks. Their core mechanism relies on the restricted presumption of degradation prior to the additive noise operation. However, …
Image RestorationImage DeblurringOptimizing Diffusion Priors in Image Reconstruction from a Single Observation
While diffusion priors generate high-quality posterior samples across many inverse problems, they are often trained on limited training sets or purely simulated data, thus inheriting the errors and biases of these underl…
Image ReconstructionImage DeblurringFramelet-Based Blind Image Restoration with Minimax Concave Regularization
Recovering corrupted images is one of the most challenging problems in image processing. Among various restoration tasks, blind image deblurring has been extensively studied due to its practical importance and inherent d…
Image RestorationImage DeblurringSaturation-Aware Space-Variant Blind Image Deblurring
This paper presents a novel saturation aware space variant blind image deblurring framework designed to address challenges posed by saturated pixels in deblurring under high dynamic range and low light conditions. The pr…
Image DeblurringSMFD-UNet: Semantic Face Mask Is The Only Thing You Need To Deblur Faces
For applications including facial identification, forensic analysis, photographic improvement, and medical imaging diagnostics, facial image deblurring is an essential chore in computer vision allowing the restoration of…
Image RestorationImage DeblurringUnblur-SLAM: Dense Neural SLAM for Blurry Inputs
We propose Unblur-SLAM, a novel RGB SLAM pipeline for sharp 3D reconstruction from blurred image inputs. In contrast to previous work, our approach is able to handle different types of blur and demonstrates state-of-the-…
3D ReconstructionImage DeblurringPose EstimationAdaptive regularization parameter selection for high-dimensional inverse problems: A Bayesian approach with Tucker low-rank constraints
This paper introduces a novel variational Bayesian method that integrates Tucker decomposition for efficient high-dimensional inverse problem solving. The method reduces computational complexity by transforming variation…
Image DeblurringBluRef: Unsupervised Image Deblurring with Dense-Matching References
This paper introduces a novel unsupervised approach for image deblurring that utilizes a simple process for training data collection, thereby enhancing the applicability and effectiveness of deblurring methods. Our techn…
Image DeblurringUHD Image Deblurring via Autoregressive Flow with Ill-conditioned Constraints
Ultra-high-definition (UHD) image deblurring poses significant challenges for UHD restoration methods, which must balance fine-grained detail recovery and practical inference efficiency. Although prominent discriminative…
Image DeblurringGeneric Camera Calibration using Blurry Images
Camera calibration is the foundation of 3D vision. Generic camera calibration can yield more accurate results than parametric cam era calibration. However, calibrating a generic camera model using printed calibration boa…
Image DeblurringNeural Discrimination-Prompted Transformers for Efficient UHD Image Restoration and Enhancement
We propose a simple yet effective UHDPromer, a neural discrimination-prompted Transformer, for Ultra-High-Definition (UHD) image restoration and enhancement. Our UHDPromer is inspired by an interesting observation that t…
Low-Light Image EnhancementComputational EfficiencyImage RestorationImage DeblurringGSNR: Graph Smooth Null-Space Representation for Inverse Problems
Inverse problems in imaging are ill-posed, leading to infinitely many solutions consistent with the measurements due to the non-trivial null-space of the sensing matrix. Common image priors promote solutions on the gener…
Image Super-ResolutionImage DeblurringEndoCaver: Handling Fog, Blur and Glare in Endoscopic Images via Joint Deblurring-Segmentation
Endoscopic image analysis is vital for colorectal cancer screening, yet real-world conditions often suffer from lens fogging, motion blur, and specular highlights, which severely compromise automated polyp detection. We …
Image DeblurringTowards Efficient Image Deblurring for Edge Deployment
Image deblurring is a critical stage in mobile image signal processing pipelines, where the ability to restore fine structures and textures must be balanced with real-time constraints on edge devices. While recent deep n…
Image DeblurringNanoSD: Edge Efficient Foundation Model for Real Time Image Restoration
Latent diffusion models such as Stable Diffusion 1.5 offer strong generative priors that are highly valuable for image restoration, yet their full pipelines remain too computationally heavy for deployment on edge devices…
Monocular Depth EstimationImage Super-ResolutionImage RestorationImage Deblurring