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Denoising
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Denoising is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of denoising is to recover the original image, which is considered to be noise-free, from a noisy observation.
<span style="color:grey; opacity: 0.6">( Image credit: Beyond a Gaussian Denoiser )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
ECGDeDRDNet: A deep learning-based method for Electrocardiogram noise removal using a double recurrent dense network
Survey of Video Diffusion Models: Foundations, Implementations, and Applications
Aerial Active STAR-RIS-assisted Satellite-Terrestrial Covert Communications
An Automated Pipeline for Few-Shot Bird Call Classification: A Case Study with the Tooth-Billed Pigeon
Self-Controlled Diffusion for Denoising in Scientific Imaging
PIV-FlowDiffuser:Transfer-learning-based denoising diffusion models for PIV
DyST-XL: Dynamic Layout Planning and Content Control for Compositional Text-to-Video Generation
Learned Primal Dual Splitting for Self-Supervised Noise-Adaptive MRI Reconstruction
A Self-supervised Learning Method for Raman Spectroscopy based on Masked Autoencoders
FlowLoss: Dynamic Flow-Conditioned Loss Strategy for Video Diffusion Models
Teach Me How to Denoise: A Universal Framework for Denoising Multi-modal Recommender Systems via Guided Calibration
An Artificial Intelligence Enabled Signature Estimation of Dual Wideband Systems in Ultra-Low Signal-to-Noise Ratio
Generative emulation of chaotic dynamics with coherent prior
Text-Audio-Visual-conditioned Diffusion Model for Video Saliency Prediction
Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving Safety
Filter2Noise: Interpretable Self-Supervised Single-Image Denoising for Low-Dose CT with Attention-Guided Bilateral Filtering
OBIFormer: A Fast Attentive Denoising Framework for Oracle Bone Inscriptions
WeatherGen: A Unified Diverse Weather Generator for LiDAR Point Clouds via Spider Mamba Diffusion
Adaptive Long-term Embedding with Denoising and Augmentation for Recommendation
Set You Straight: Auto-Steering Denoising Trajectories to Sidestep Unwanted Concepts
TTRD3: Texture Transfer Residual Denoising Dual Diffusion Model for Remote Sensing Image Super-Resolution
Denoising and Reconstruction of Nonlinear Dynamics using Truncated Reservoir Computing
Exploring Video-Based Driver Activity Recognition under Noisy Labels
Generative Recommendation with Continuous-Token Diffusion
Towards Explainable Fusion and Balanced Learning in Multimodal Sentiment Analysis
Deep Generative Models for Bayesian Inference on High-Rate Sensor Data: Applications in Automotive Radar and Medical Imaging
Modality-Independent Explainable Detection of Inaccurate Organ Segmentations Using Denoising Autoencoders
The Tenth NTIRE 2025 Image Denoising Challenge Report
Generalization through variance: how noise shapes inductive biases in diffusion models
Efficient and Robust Remote Sensing Image Denoising Using Randomized Approximation of Geodesics' Gramian on the Manifold Underlying the Patch Space
IlluSign: Illustrating Sign Language Videos by Leveraging the Attention Mechanism
Bringing together invertible UNets with invertible attention modules for memory-efficient diffusion models
InterAnimate: Taming Region-aware Diffusion Model for Realistic Human Interaction Animation
Cross-Frequency Implicit Neural Representation with Self-Evolving Parameters
AgentPolyp: Accurate Polyp Segmentation via Image Enhancement Agent
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.