Denoising

1835 papers with code • 5 benchmarks • 20 datasets

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 )

Libraries

Use these libraries to find Denoising models and implementations

ModWaveMLP: MLP-Based Mode Decomposition and Wavelet Denoising Model to Defeat Complex Structures in Traffic Forecasting

Kqingzheng/ModWaveMLP The 38th Annual AAAI Conference on Artificial Intelligence 2024

Additionally, when handling traffic data, researchers tend to manually design the model structure based on the data features, which makes the structure of traffic prediction redundant and the model generalizability limited.

3
01 Jul 2024

SingularTrajectory: Universal Trajectory Predictor Using Diffusion Model

inhwanbae/singulartrajectory 27 Mar 2024

In this paper, we propose SingularTrajectory, a diffusion-based universal trajectory prediction framework to reduce the performance gap across the five tasks.

11
27 Mar 2024

Ship in Sight: Diffusion Models for Ship-Image Super Resolution

luigisigillo/shipinsight 27 Mar 2024

In this context, our method explores in depth the problem of ship image super resolution, which is crucial for coastal and port surveillance.

1
27 Mar 2024

Self-Rectifying Diffusion Sampling with Perturbed-Attention Guidance

KU-CVLAB/Perturbed-Attention-Guidance 26 Mar 2024

These techniques are often not applicable in unconditional generation or in various downstream tasks such as image restoration.

74
26 Mar 2024

Noise2Noise Denoising of CRISM Hyperspectral Data

rob-platt/n2n4m 26 Mar 2024

Hyperspectral data acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) have allowed for unparalleled mapping of the surface mineralogy of Mars.

3
26 Mar 2024

Building Bridges across Spatial and Temporal Resolutions: Reference-Based Super-Resolution via Change Priors and Conditional Diffusion Model

dongrunmin/refdiff 26 Mar 2024

Specifically, we inject the priors into the denoising model to improve the utilization of reference information in unchanged areas and regulate the reconstruction of semantically relevant content in changed areas.

1
26 Mar 2024

Denoising Table-Text Retrieval for Open-Domain Question Answering

deokhk/dotter 26 Mar 2024

Previous studies in table-text open-domain question answering have two common challenges: firstly, their retrievers can be affected by false-positive labels in training datasets; secondly, they may struggle to provide appropriate evidence for questions that require reasoning across the table.

1
26 Mar 2024

Make-Your-Anchor: A Diffusion-based 2D Avatar Generation Framework

ictmcg/make-your-anchor 25 Mar 2024

We adopt a two-stage training strategy for the diffusion model, effectively binding movements with specific appearances.

116
25 Mar 2024

Multi-Scale Texture Loss for CT denoising with GANs

francescodifeola/denotextureloss 25 Mar 2024

To grasp highly complex and non-linear textural relationships in the training process, this work presents a loss function that leverages the intrinsic multi-scale nature of the Gray-Level-Co-occurrence Matrix (GLCM).

0
25 Mar 2024

AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation

c-yn/adair 21 Mar 2024

Our approach is motivated by the observation that different degradation types impact the image content on different frequency subbands, thereby requiring different treatments for each restoration task.

40
21 Mar 2024