SOTAVerified

Denoising

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.

( Image credit: Beyond a Gaussian Denoiser )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 6651–6675 of 7282 papers

TitleStatusHype
Distributed Cartesian Power Graph Segmentation for Graphon Estimation—0
Distributed Evolution of Deep Autoencoders—0
View Blind-spot as Inpainting: Self-Supervised Denoising with Mask Guided Residual Convolution—0
Distribution-Aligned Diffusion for Human Mesh Recovery—0
Distribution Conditional Denoising: A Flexible Discriminative Image Denoiser—0
ALA: Naturalness-aware Adversarial Lightness Attack—0
AI Security for Geoscience and Remote Sensing: Challenges and Future Trends—0
DiT-Head: High-Resolution Talking Head Synthesis using Diffusion Transformers—0
DIVA: Deep Unfolded Network from Quantum Interactive Patches for Image Restoration—0
DiVAE: Photorealistic Images Synthesis with Denoising Diffusion Decoder—0
Diverse Score Distillation—0
TexGen: Text-Guided 3D Texture Generation with Multi-view Sampling and Resampling—0
Divide, Denoise, and Defend against Adversarial Attacks—0
3D Scene Diffusion Guidance using Scene Graphs—0
AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air—0
DMOSpeech: Direct Metric Optimization via Distilled Diffusion Model in Zero-Shot Speech Synthesis—0
DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model—0
Aircraft Radar Altimeter Interference Mitigation Through a CNN-Layer Only Denoising Autoencoder Architecture—0
DNN Task Assignment in UAV Networks: A Generative AI Enhanced Multi-Agent Reinforcement Learning Approach—0
DN-ResNet: Efficient Deep Residual Network for Image Denoising—0
Structure Disruption: Subverting Malicious Diffusion-Based Inpainting via Self-Attention Query Perturbation—0
Structured Object Language Modeling (SoLM): Native Structured Objects Generation Conforming to Complex Schemas with Self-Supervised Denoising—0
DOA Estimation by DNN-based Denoising and Dereverberation from Sound Intensity Vector—0
Do Bayesian imaging methods report trustworthy probabilities?—0
Document Enhancement System Using Auto-encoders—0
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All datasetsDarmstadt Noise DatasetDIV2KDNDiris

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81—Unverified
2Pixel-shuffling DownsamplingPSNR38.4—Unverified
3TWSCPSNR37.93—Unverified
4CBDNet(Syn)PSNR37.57—Unverified
5MCWNNMPSNR37.38—Unverified
6Han et alPSNR35.95—Unverified
7FFDNetPSNR34.4—Unverified
8TNRDPSNR33.65—Unverified
9CDnCNN-BPSNR32.43—Unverified
10NLRNPSNR30.8—Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92—Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64—Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61—Unverified