Papers Super-Resolution
“Super-Resolution” 태그가 달린 논문 3,874편 · 필터 해제
SpectraLift: Physics-Guided Spectral-Inversion Network for Self-Supervised Hyperspectral Image Super-Resolution
High-spatial-resolution hyperspectral images (HSI) are essential for applications such as remote sensing and medical imaging, yet HSI sensors inherently trade spatial detail for spectral richness. Fusing high-spatial-res…
Hyperspectral Image Super-ResolutionImage Super-ResolutionSpectral ReconstructionSSIM+1IM-LUT: Interpolation Mixing Look-Up Tables for Image Super-Resolution
Super-resolution (SR) has been a pivotal task in image processing, aimed at enhancing image resolution across various applications. Recently, look-up table (LUT)-based approaches have attracted interest due to their effi…
Image Super-ResolutionSuper-ResolutionPanoDiff-SR: Synthesizing Dental Panoramic Radiographs using Diffusion and Super-resolution
There has been increasing interest in the generation of high-quality, realistic synthetic medical images in recent years. Such synthetic datasets can mitigate the scarcity of public datasets for artificial intelligence r…
Super-ResolutionHNOSeg-XS: Extremely Small Hartley Neural Operator for Efficient and Resolution-Robust 3D Image Segmentation
In medical image segmentation, convolutional neural networks (CNNs) and transformers are dominant. For CNNs, given the local receptive fields of convolutional layers, long-range spatial correlations are captured through …
GPUImage SegmentationMedical Image SegmentationSemantic Segmentation+14KAgent: Agentic Any Image to 4K Super-Resolution
We present 4KAgent, a unified agentic super-resolution generalist system designed to universally upscale any image to 4K resolution (and even higher, if applied iteratively). Our system can transform images from extremel…
4kImage Quality AssessmentSuper-ResolutionEAMamba: 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+2Leveraging Vision-Language Models to Select Trustworthy Super-Resolution Samples Generated by Diffusion Models
Super-resolution (SR) is an ill-posed inverse problem with many feasible solutions consistent with a given low-resolution image. On one hand, regressive SR models aim to balance fidelity and perceptual quality to yield a…
Semantic SimilaritySemantic Textual SimilaritySSIMSuper-ResolutionUnsupervised Image Super-Resolution Reconstruction Based on Real-World Degradation Patterns
The training of real-world super-resolution reconstruction models heavily relies on datasets that reflect real-world degradation patterns. Extracting and modeling degradation patterns for super-resolution reconstruction …
Image Super-ResolutionSuper-ResolutionTranslationEfficient Feedback Gate Network for Hyperspectral Image Super-Resolution
Even without auxiliary images, single hyperspectral image super-resolution (SHSR) methods can be designed to improve the spatial resolution of hyperspectral images. However, failing to explore coherence thoroughly along …
Hyperspectral Image Super-ResolutionImage Super-ResolutionSuper-ResolutionSTAR-Pose: Efficient Low-Resolution Video Human Pose Estimation via Spatial-Temporal Adaptive Super-Resolution
Human pose estimation in low-resolution videos presents a fundamental challenge in computer vision. Conventional methods either assume high-quality inputs or employ computationally expensive cascaded processing, which li…
Pose EstimationSuper-ResolutionR3eVision: 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+5FADPNet: Frequency-Aware Dual-Path Network for Face Super-Resolution
Face super-resolution (FSR) under limited computational costs remains an open problem. Existing approaches typically treat all facial pixels equally, resulting in suboptimal allocation of computational resources and degr…
MambaSuper-ResolutionExploring Diffusion with Test-Time Training on Efficient Image Restoration
Image restoration faces challenges including ineffective feature fusion, computational bottlenecks and inefficient diffusion processes. To address these, we propose DiffRWKVIR, a novel framework unifying Test-Time Traini…
DenoisingImage RestorationSSIMSuper-ResolutionUnsupervised 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-ResolutionCompressed Video Super-Resolution based on Hierarchical Encoding
This paper presents a general-purpose video super-resolution (VSR) method, dubbed VSR-HE, specifically designed to enhance the perceptual quality of compressed content. Targeting scenarios characterized by heavy compress…
QuantizationSuper-ResolutionVideo Super-ResolutionDoA Estimation using MUSIC with Range/Doppler Multiplexing for MIMO-OFDM Radar
Sensing emerges as a critical challenge in 6G networks, which require simultaneous communication and target sensing capabilities. State-of-the-art super-resolution techniques for the direction of arrival (DoA) estimation…
parameter estimationSuper-ResolutionGITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations
We present a novel graph-informed transformer operator (GITO) architecture for learning complex partial differential equation systems defined on irregular geometries and non-uniform meshes. GITO consists of two main modu…
Graph Neural NetworkSuper-ResolutionExploiting the Exact Denoising Posterior Score in Training-Free Guidance of Diffusion Models
The success of diffusion models has driven interest in performing conditional sampling via training-free guidance of the denoising process to solve image restoration and other inverse problems. A popular class of methods…
ColorizationDenoisingImage RestorationSuper-ResolutionESRPCB: an Edge guided Super-Resolution model and Ensemble learning for tiny Printed Circuit Board Defect detection
Printed Circuit Boards (PCBs) are critical components in modern electronics, which require stringent quality control to ensure proper functionality. However, the detection of defects in small-scale PCBs images poses sign…
Defect DetectionEnsemble LearningSuper-ResolutionEfficient Star Distillation Attention Network for Lightweight Image Super-Resolution
In recent years, the performance of lightweight Single-Image Super-Resolution (SISR) has been improved significantly with the application of Convolutional Neural Networks (CNNs) and Large Kernel Attention (LKA). However,…
Image Super-ResolutionRepresentation LearningSuper-Resolution