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

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Showing 201–250 of 7282 papers

TitleStatusHype
FlowDiffuser: Advancing Optical Flow Estimation with Diffusion ModelsCode2
Dreamer XL: Towards High-Resolution Text-to-3D Generation via Trajectory Score MatchingCode2
An End-to-End Robust Point Cloud Semantic Segmentation Network with Single-Step Conditional Diffusion ModelsCode2
CGVQM+D: Computer Graphics Video Quality Metric and DatasetCode2
Anomaly Detection with Conditioned Denoising Diffusion ModelsCode2
FORA: Fast-Forward Caching in Diffusion Transformer AccelerationCode2
DnLUT: Ultra-Efficient Color Image Denoising via Channel-Aware Lookup TablesCode2
Dita: Scaling Diffusion Transformer for Generalist Vision-Language-Action PolicyCode2
DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape GenerationCode2
dKV-Cache: The Cache for Diffusion Language ModelsCode2
DocDiff: Document Enhancement via Residual Diffusion ModelsCode2
EDICT: Exact Diffusion Inversion via Coupled TransformationsCode2
Adaptive Guidance: Training-free Acceleration of Conditional Diffusion ModelsCode2
GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New InsightsCode2
All-In-One Medical Image Restoration via Task-Adaptive RoutingCode2
Invisible Image Watermarks Are Provably Removable Using Generative AICode2
Generative Time Series Forecasting with Diffusion, Denoise, and DisentanglementCode2
Gen-L-Video: Multi-Text to Long Video Generation via Temporal Co-DenoisingCode2
Aligning Text-to-Image Diffusion Models with Reward BackpropagationCode2
GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly DetectionCode2
Guidance with Spherical Gaussian Constraint for Conditional DiffusionCode2
BlockFusion: Expandable 3D Scene Generation using Latent Tri-plane ExtrapolationCode2
DiGress: Discrete Denoising diffusion for graph generationCode2
DiSA: Diffusion Step Annealing in Autoregressive Image GenerationCode2
HSIGene: A Foundation Model For Hyperspectral Image GenerationCode2
HumanMAC: Masked Motion Completion for Human Motion PredictionCode2
Diffusion Transformer PolicyCode2
CoLaDa: A Collaborative Label Denoising Framework for Cross-lingual Named Entity RecognitionCode2
DiffusionTrack: Diffusion Model For Multi-Object TrackingCode2
IDOL: Unified Dual-Modal Latent Diffusion for Human-Centric Joint Video-Depth GenerationCode2
CoMoSpeech: One-Step Speech and Singing Voice Synthesis via Consistency ModelCode2
Immiscible Diffusion: Accelerating Diffusion Training with Noise AssignmentCode2
Collaborative Diffusion for Multi-Modal Face Generation and EditingCode2
AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq ModelCode2
Diffusion Recommender ModelCode2
Improving Diffusion Inverse Problem Solving with Decoupled Noise AnnealingCode2
Diffusion-Sharpening: Fine-tuning Diffusion Models with Denoising Trajectory SharpeningCode2
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial OptimizationCode2
Diffusion Models in Vision: A SurveyCode2
Compressed Image Generation with Denoising Diffusion Codebook ModelsCode2
Diffusion Predictive Control with ConstraintsCode2
Compression-Aware One-Step Diffusion Model for JPEG Artifact RemovalCode2
InterGen: Diffusion-based Multi-human Motion Generation under Complex InteractionsCode2
Graph Diffusion Transformers for Multi-Conditional Molecular GenerationCode2
Towards Stabilized and Efficient Diffusion Transformers through Long-Skip-Connections with Spectral ConstraintsCode2
Diffusion models as plug-and-play priorsCode2
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse ProblemsCode2
Large Language Models are Efficient Learners of Noise-Robust Speech RecognitionCode2
Latent Video Diffusion Models for High-Fidelity Long Video GenerationCode2
DiffusionInst: Diffusion Model for Instance SegmentationCode2
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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