Papers Deblurring
“Deblurring” 태그가 달린 논문 999편 · 필터 해제
Generative Latent Kernel Modeling for Blind Motion Deblurring
Deep prior-based approaches have demonstrated remarkable success in blind motion deblurring (BMD) recently. These methods, however, are often limited by the high non-convexity of the underlying optimization process in BM…
DeblurringGenerative Adversarial NetworkSensitivityEAMamba: Efficient All-Around Vision State Space Model for Image Restoration
Image restoration is a key task in low-level computer vision that aims to reconstruct high-quality images from degraded inputs. The emergence of Vision Mamba, which draws inspiration from the advanced state space model M…
AllDeblurringDenoisingImage Restoration+2Dynamic Bandwidth Allocation for Hybrid Event-RGB Transmission
Event cameras asynchronously capture pixel-level intensity changes with extremely low latency. They are increasingly used in conjunction with RGB cameras for a wide range of vision-related applications. However, a major …
DeblurringInformativenessVisual-Instructed Degradation Diffusion for All-in-One Image Restoration
Image restoration tasks like deblurring, denoising, and dehazing usually need distinct models for each degradation type, restricting their generalization in real-world scenarios with mixed or unknown degradations. In thi…
AllDeblurringDenoisingImage RestorationR3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level Vision
Neural rendering methods such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have achieved significant progress in photorealistic 3D scene reconstruction and novel view synthesis. However, most existin…
3DGS3D Reconstruction3D Scene ReconstructionAutonomous Driving+5Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching
This work addresses image restoration tasks through the lens of inverse problems using unpaired datasets. In contrast to traditional approaches -- which typically assume full knowledge of the forward model or access to p…
Blind Super-ResolutionDeblurringImage RestorationSuper-ResolutionRestoring Gaussian Blurred Face Images for Deanonymization Attacks
Gaussian blur is widely used to blur human faces in sensitive photos before the photos are posted on the Internet. However, it is unclear to what extent the blurred faces can be restored and used to re-identify the perso…
DeblurringFace AnonymizationMemorizationPlug-and-Play Linear Attention for Pre-trained Image and Video Restoration Models
Multi-head self-attention (MHSA) has become a core component in modern computer vision models. However, its quadratic complexity with respect to input length poses a significant computational bottleneck in real-time and …
CPUDeblurringDenoisingGPU+2Multi-Step Guided Diffusion for Image Restoration on Edge Devices: Toward Lightweight Perception in Embodied AI
Diffusion models have shown remarkable flexibility for solving inverse problems without task-specific retraining. However, existing approaches such as Manifold Preserving Guided Diffusion (MPGD) apply only a single gradi…
DeblurringDenoisingImage RestorationSuper-ResolutionEV-LayerSegNet: Self-supervised Motion Segmentation using Event Cameras
Event cameras are novel bio-inspired sensors that capture motion dynamics with much higher temporal resolution than traditional cameras, since pixels react asynchronously to brightness changes. They are therefore better …
DeblurringMotion SegmentationOptical Flow EstimationSegmentation+1On Inverse Problems, Parameter Estimation, and Domain Generalization
Signal restoration and inverse problems are key elements in most real-world data science applications. In the past decades, with the emergence of machine learning methods, inversion of measurements has become a popular s…
DeblurringDomain GeneralizationImage Deblurringparameter estimationEfficient RAW Image Deblurring with Adaptive Frequency Modulation
Image deblurring plays a crucial role in enhancing visual clarity across various applications. Although most deep learning approaches primarily focus on sRGB images, which inherently lose critical information during the …
Computational EfficiencyDeblurringImage DeblurringURWKV: Unified RWKV Model with Multi-state Perspective for Low-light Image Restoration
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. …
DeblurringImage EnhancementImage RestorationLow-Light Image EnhancementPlug-and-Play Posterior Sampling for Blind Inverse Problems
We introduce Blind Plug-and-Play Diffusion Models (Blind-PnPDM) as a novel framework for solving blind inverse problems where both the target image and the measurement operator are unknown. Unlike conventional methods th…
Blind Image DeblurringDeblurringDenoisingImage Deblurring+1SpikeGen: Generative Framework for Visual Spike Stream Processing
Neuromorphic Visual Systems, such as spike cameras, have attracted considerable attention due to their ability to capture clear textures under dynamic conditions. This capability effectively mitigates issues related to m…
DeblurringNovel View SynthesisVideo DeblurringJoint Flow And Feature Refinement Using Attention For Video Restoration
Recent advancements in video restoration have focused on recovering high-quality video frames from low-quality inputs. Compared with static images, the performance of video restoration significantly depends on efficient …
DeblurringDenoisingPhilosophySuper-Resolution+1Deep Learning-Driven Ultra-High-Definition Image Restoration: A Survey
Ultra-high-definition (UHD) image restoration aims to specifically solve the problem of quality degradation in ultra-high-resolution images. Recent advancements in this field are predominantly driven by deep learning-bas…
DeblurringDeep LearningImage RestorationRain Removal+1Linear Convergence of Plug-and-Play Algorithms with Kernel Denoisers
The use of denoisers for image reconstruction has shown significant potential, especially for the Plug-and-Play (PnP) framework. In PnP, a powerful denoiser is used as an implicit regularizer in proximal algorithms such …
DeblurringImage ReconstructionDegradation-Aware Feature Perturbation for All-in-One Image Restoration
All-in-one image restoration aims to recover clear images from various degradation types and levels with a unified model. Nonetheless, the significant variations among degradation types present challenges for training a …
AllDeblurringDenoisingImage Dehazing+5UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights
Recent advances in data-centric deep generative models have led to significant progress in solving inverse imaging problems. However, these models (e.g., diffusion models (DMs)) typically require large amounts of fully s…
DeblurringSuper-Resolution