Browse > Computer Vision > Denoising

Denoising Edit

305 papers with code · Computer Vision

Denoising is the task of removing noise from an image.

( Image credit: Beyond a Gaussian Denoiser )

TREND DATASET BEST METHOD PAPER TITLE PAPER CODE COMPARE

Enhancing Intrinsic Adversarial Robustness via Feature Pyramid Decoder

Whereas adversarial training is employed as the main defence strategy against specific adversarial samples, it has limited generalization capability and incurs excessive time complexity.

5
06 May 2020

DenoiSeg: Joint Denoising and Segmentation

6 May 2020juglab/DenoiSeg

Here we propose DenoiSeg, a new method that can be trained end-to-end on only a few annotated ground truth segmentations.

5
06 May 2020

Comparison of Image Quality Models for Optimization of Image Processing Systems

4 May 2020dingkeyan93/IQA-optimization

The performance of objective image quality assessment (IQA) models has been evaluated primarily by comparing model predictions to human judgments.

31
04 May 2020

SCRDet++: Detecting Small, Cluttered and Rotated Objects via Instance-Level Feature Denoising and Rotation Loss Smoothing

28 Apr 2020Thinklab-SJTU/R3Det_Tensorflow

Instance-level denoising on the feature map is performed to enhance the detection to small and cluttered objects.

173
28 Apr 2020

Pyramid Attention Networks for Image Restoration

28 Apr 2020SHI-Labs/Pyramid-Attention-Networks

Self-similarity refers to the image prior widely used in image restoration algorithms that small but similar patterns tend to occur at different locations and scales.

79
28 Apr 2020

Attention Prior for Real Image Restoration

26 Apr 2020saeed-anwar/R2Net

Furthermore, the evaluation in terms of quantitative metrics and visual quality for four restoration tasks i. e. Denoising, Super-resolution, Raindrop Removal, and JPEG Compression on 11 real degraded datasets against more than 30 state-of-the-art algorithms demonstrate the superiority of our R$^2$Net.

12
26 Apr 2020

Learning an Adaptive Model for Extreme Low-light Raw Image Processing

22 Apr 2020505030475/ExtremeLowLight

Furthermore, those tests illustrate that the proposed method is able to adaptively control the global image brightness according to the content of the image scene.

11
22 Apr 2020

Microscopy Image Restoration using Deep Learning on W2S

22 Apr 2020mchatton/w2s-tensorflow

We develop a deep learning algorithm based on the networks and method described in the recent W2S paper to solve a joint denoising and super-resolution problem.

10
22 Apr 2020

Unsupervised Opinion Summarization with Noising and Denoising

21 Apr 2020rktamplayo/DenoiseSum

We create a synthetic dataset from a corpus of user reviews by sampling a review, pretending it is a summary, and generating noisy versions thereof which we treat as pseudo-review input.

5
21 Apr 2020

Learning from Rules Generalizing Labeled Exemplars

Empirical evaluation on five different tasks shows that (1) our algorithm is more accurate than several existing methods of learning from a mix of clean and noisy supervision, and (2) the coupled rule-exemplar supervision is effective in denoising rules.

13
13 Apr 2020