https://github.com/Mind23-2/MindCode-3/tree/main/llnet
LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement
Papers with Code 아카이브
Denoising
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 6
- 평가표
- 6
- 보존된 평가 기록
- 15
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.
<span style="color:grey; opacity: 0.6">( Image credit: Beyond a Gaussian Denoiser )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Mind23-2/MindCode-5/tree/main/RDN
https://github.com/MindCode-4/code-13/tree/main/WaveCRN-master
WaveCRN: An Efficient Convolutional Recurrent Neural Network for End-to-end Speech Enhancement
https://github.com/MindCode-4/code-3/tree/main/deta
https://github.com/MindCode-4/code-5/tree/main/t5
ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning
https://github.com/MindCode-4/code-5/tree/main/vit_hybrid
Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion Model
https://github.com/MindCode-4/code-7/tree/main/gaussian_adaptive_attention
https://github.com/MindCode-4/code-8/tree/main/Projected-Distribution
https://github.com/MindSpore-MS-Code2/code0/tree/main/DnCNN
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/MindSpore-paper-code-2/code2/tree/main/RDN
https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceQualityAssessment
https://github.com/MindSpore-paper-code-3/code4/tree/main/HiFaceGAN
HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
https://github.com/MindSpore-paper-code-3/code6/tree/main/brdnet
A Multi-Head Convolutional Neural Network With Multi-path Attention improves Image Denoising
https://github.com/MindSpore-paper-code-3/code7/tree/main/FaceQualityAssessment
https://github.com/MindSpore-paper-code-3/code8/tree/main/DDM
DDM$^2$: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models
https://github.com/MindSpore-paper-code-3/code8/tree/main/DnCNN
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
https://github.com/MindSpore-paper-code-3/code8/tree/main/FaceQualityAssessment
https://github.com/MindSpore-scientific-2/code-1/tree/main/ZoneoutRNN
RNNoise-Ex: Hybrid Speech Enhancement System based on RNN and Spectral Features
https://github.com/MindSpore-scientific-2/code-10/tree/main/NBNet-Noise-Basis-Learning-for-Image-Denoising-with-Subspace-Projection
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
https://github.com/MindSpore-scientific-2/code-4/tree/main/NBNet-Noise-Basis-Learning-for-Image-Denoising-with-Subspace-Projection
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
https://github.com/MindSpore-scientific-2/code-5/tree/main/NBNet-Noise-Basis-Learning-for-Image-Denoising-with-Subspace-Projection
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
https://github.com/MindSpore-scientific-2/code-8/tree/main/NBNet-Noise-Basis-Learning-for-Image-Denoising-with-Subspace-Projection
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
https://github.com/MindSpore-scientific/code-10/tree/main/ZoneoutRNN
RNNoise-Ex: Hybrid Speech Enhancement System based on RNN and Spectral Features
https://github.com/MindSpore-scientific/code-10/tree/main/text-to-music
https://github.com/MindSpore-scientific/code-11/tree/main/Super-Resolution-for-Root-Imaging
High-Resolution Image Synthesis with Latent Diffusion Models
https://github.com/MindSpore-scientific/code-12/tree/main/Block_Model
Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
https://github.com/MindSpore-scientific/code-12/tree/main/Cybertron
DiffusionNER: Boundary Diffusion for Named Entity Recognition
https://github.com/MindSpore-scientific/code-13/tree/main/Last-Query-Transformer-RNN
RNNoise-Ex: Hybrid Speech Enhancement System based on RNN and Spectral Features
https://github.com/MindSpore-scientific/code-13/tree/main/NBNet-Noise-Basis-Learning-for-Image-Denoising-with-Subspace-Projection
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
https://github.com/MindSpore-scientific/code-14/tree/main/Sub2Full-OCT-Denoising
Sub2Full: split spectrum to boost OCT despeckling without clean data
https://github.com/MindSpore-scientific/code-2/tree/main/Sub2Full-OCT-Denoising
Sub2Full: split spectrum to boost OCT despeckling without clean data
https://github.com/MindSpore-scientific/code-2/tree/main/WaveCRN-master
WaveCRN: An Efficient Convolutional Recurrent Neural Network for End-to-end Speech Enhancement
https://github.com/MindSpore-scientific/code-5/tree/main/Projected-Distribution
https://github.com/MoSubaiei/modified-SINDy
https://github.com/MoonInTheRiver/DiffSinger
https://github.com/NMADALI97/Convexified-Convolutional-Neural-Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.