Denoising

725 papers with code • 2 benchmarks • 13 datasets

Denoising is the task of removing noise from an image.

( Image credit: Beyond a Gaussian Denoiser )

Greatest papers with code

Multilingual Denoising Pre-training for Neural Machine Translation

huggingface/transformers 22 Jan 2020

This paper demonstrates that multilingual denoising pre-training produces significant performance gains across a wide variety of machine translation (MT) tasks.

Denoising Document-level +2

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

huggingface/transformers ACL 2020

We evaluate a number of noising approaches, finding the best performance by both randomly shuffling the order of the original sentences and using a novel in-filling scheme, where spans of text are replaced with a single mask token.

Abstractive Text Summarization Denoising +5

Energy-Based Processes for Exchangeable Data

google-research/google-research ICML 2020

Recently there has been growing interest in modeling sets with exchangeability such as point clouds.

Denoising Point Cloud Generation

SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders

google-research/google-research 2 Oct 2019

We show results for extractive and human baselines to demonstrate a large abstractive gap in performance.

Abstractive Text Summarization Denoising

Unprocessing Images for Learned Raw Denoising

google-research/google-research CVPR 2019

Machine learning techniques work best when the data used for training resembles the data used for evaluation.

Image Denoising Tone Mapping

Large-scale graph representation learning with very deep GNNs and self-supervision

deepmind/deepmind-research 20 Jul 2021

In doing so, we demonstrate evidence of scalable self-supervised graph representation learning, and utility of very deep GNNs -- both very important open issues.

Denoising Graph Representation Learning

Gaussian Gated Linear Networks

deepmind/deepmind-research NeurIPS 2020

We propose the Gaussian Gated Linear Network (G-GLN), an extension to the recently proposed GLN family of deep neural networks.

Denoising Density Estimation +1

Deep Image Prior

DmitryUlyanov/deep-image-prior CVPR 2018

In this paper, we show that, on the contrary, the structure of a generator network is sufficient to capture a great deal of low-level image statistics prior to any learning.

Image Denoising Image Inpainting +3

Denoising Diffusion Probabilistic Models

labmlai/annotated_deep_learning_paper_implementations NeurIPS 2020

We present high quality image synthesis results using diffusion probabilistic models, a class of latent variable models inspired by considerations from nonequilibrium thermodynamics.

Denoising Image Generation +1