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 541550 of 7282 papers

TitleStatusHype
Continual Learning of Diffusion Models with Generative DistillationCode1
Context-Aware Pseudo-Label Refinement for Source-Free Domain Adaptive Fundus Image SegmentationCode1
A Mixture-Based Framework for Guiding Diffusion ModelsCode1
Content-Noise Complementary Learning for Medical Image DenoisingCode1
Continuous Speculative Decoding for Autoregressive Image GenerationCode1
Diffusion Models Beat GANs on Image ClassificationCode1
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be ConsistentCode1
Diffusion Model Guided Sampling with Pixel-Wise Aleatoric Uncertainty EstimationCode1
Consistency Guided Knowledge Retrieval and Denoising in LLMs for Zero-shot Document-level Relation Triplet ExtractionCode1
Diffusion Model is Secretly a Training-free Open Vocabulary Semantic SegmenterCode1
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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