Image Denoising
21개 벤치마크 · 논문 1,317편 · 이 태스크의 논문 보기 →
Benchmarks
SIDD
DND
ELD SonyA7S2 x200
SID SonyA7S2 x250
ELD SonyA7S2 x100
SID x100
SID x300
SID SonyA7S2 x100
Urban100 sigma50
urban100 sigma15
BSD68 sigma50
SID SonyA7S2 x300
Urban100 sigma25
BSD68 sigma30
FFHQ
FMD
Nam
PolyU
Most implemented
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Learning to See in the Dark
Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
Deep Image Prior
Simple Baselines for Image Restoration
Restormer: Efficient Transformer for High-Resolution Image Restoration
Papers
Efficient 3D Whole-Body PET Image Denoising via Conditional Rectified Flow With Optimized Sampling Strategy
Reducing radiation exposure in Positron Emission Tomography (PET) is important for patient safety; however, ultra-low-dose imaging suffers from severe noise, which may affect diagnostic interpretation without appropriate…
Computational EfficiencyImage EnhancementImage DenoisingTT-net: Quantum Inspired Tensor Network Denoising in Conditional GANs
Developed as a workhorse for classical simulations of quantum algorithms and quantum many-body systems, Tensor Network methods have entered the scientific mainstream in quantum physics. Among various types of tensor netw…
Image DenoisingVLM- and LLM-Driven Multi-Agent System for PET Image Denoising
Positron emission tomography (PET) imaging suffers from limited spatial resolution and low signal-to-noise ratio, which can compromise quantitative accuracy and lesion detectability. Deep learning-based denoising methods…
Image DenoisingLiteKD-Net: Lightweight Knowledge-Distilled Network for Mobile Image Denoising
Mobile image denoising requires both good restoration quality and low computational cost. In addition, it's annoying to collect large-scale LQ-GT clean pairs. As a result, we propose LiteKD-Net, a lightweight knowledge-d…
Computational EfficiencyKnowledge DistillationImage DenoisingYeTI: You Only Need Two Noisy Images for Real-World sRGB Noise Generation
Real-world sRGB image denoising remains challenging due to the nonlinear characteristics of sensor noise and the difficulty of acquiring aligned clean-noisy image pairs. Supervised denoisers often overfit to limited pair…
Image DenoisingBridging Interleaved Multi-Modal Reasoning as a Unified Decision Process
Unified multi-modal models (UMMs) have shown promising interleaved text-image reasoning capabilities, yet effectively optimizing such multi-turn generation via reinforcement learning (RL) remains an open challenge. Exist…
Reinforcement LearningSpatial ReasoningImage GenerationImage Denoising