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

Showing 376400 of 7282 papers

TitleStatusHype
DiffusionDepth: Diffusion Denoising Approach for Monocular Depth EstimationCode2
Mobius: Text to Seamless Looping Video Generation via Latent ShiftCode2
Diffusion-based Visual Anagram as Multi-task LearningCode2
Compressed Image Generation with Denoising Diffusion Codebook ModelsCode2
DiffusionBERT: Improving Generative Masked Language Models with Diffusion ModelsCode2
Diffusion360: Seamless 360 Degree Panoramic Image Generation based on Diffusion ModelsCode2
MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly DetectionCode2
CoMoSpeech: One-Step Speech and Singing Voice Synthesis via Consistency ModelCode2
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly DetectionCode2
DiffTalk: Crafting Diffusion Models for Generalized Audio-Driven Portraits AnimationCode2
Diffusion^2: Dynamic 3D Content Generation via Score Composition of Video and Multi-view Diffusion ModelsCode2
BlockFusion: Expandable 3D Scene Generation using Latent Tri-plane ExtrapolationCode2
Diffusion-based Generation, Optimization, and Planning in 3D ScenesCode2
DiffIR: Efficient Diffusion Model for Image RestorationCode2
A DeNoising FPN With Transformer R-CNN for Tiny Object DetectionCode2
DiffiT: Diffusion Vision Transformers for Image GenerationCode2
All-In-One Medical Image Restoration via Task-Adaptive RoutingCode2
Aligning Text-to-Image Diffusion Models with Reward BackpropagationCode2
Optimal Weighted Convolution for Classification and DenosingCode2
DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration ModelsCode2
PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-ResolutionCode2
Exposure Bracketing Is All You Need For A High-Quality ImageCode2
AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq ModelCode2
DiffLoc: Diffusion Model for Outdoor LiDAR LocalizationCode2
DiffAssemble: A Unified Graph-Diffusion Model for 2D and 3D ReassemblyCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81Unverified
2Pixel-shuffling DownsamplingPSNR38.4Unverified
3TWSCPSNR37.93Unverified
4CBDNet(Syn)PSNR37.57Unverified
5MCWNNMPSNR37.38Unverified
6Han et alPSNR35.95Unverified
7FFDNetPSNR34.4Unverified
8TNRDPSNR33.65Unverified
9CDnCNN-BPSNR32.43Unverified
10NLRNPSNR30.8Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61Unverified