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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Mind23-2/MindCode-101/tree/main/llnet

LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement

https://github.com/Mind23-2/MindCode-132

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

https://github.com/Mind23-2/MindCode-148

ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning

https://github.com/Mind23-2/MindCode-160

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

https://github.com/Mind23-2/MindCode-171

Denoising Diffusion Implicit Models

https://github.com/Mind23-2/MindCode-3/tree/main/HiFaceGAN

HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment

https://github.com/Mind23-2/MindCode-3/tree/main/IPT

Pre-Trained Image Processing Transformer

https://github.com/Mind23-2/MindCode-3/tree/main/IndexNet

Index Network

https://github.com/Mind23-2/MindCode-3/tree/main/LearningToSeeInTheDark

Learning to See in the Dark

https://github.com/Mind23-2/MindCode-3/tree/main/Neighbor2Neighbor

Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images

https://github.com/Mind23-2/MindCode-3/tree/main/llnet

LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement

https://github.com/Mind23-2/MindCode-5/tree/main/RDN

Residual Dense Network for Image Super-Resolution

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

DETA: Denoised Task Adaptation for Few-Shot Learning

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

Gaussian Gated Linear Networks

https://github.com/MindCode-4/code-8/tree/main/Projected-Distribution

Projected Distribution Loss for Image Enhancement

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

Residual Dense Network for Image Super-Resolution

https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceQualityAssessment

Assessment of Data Consistency through Cascades of Independently Recurrent Inference Machines for fast and robust accelerated MRI reconstruction

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

Assessment of Data Consistency through Cascades of Independently Recurrent Inference Machines for fast and robust accelerated MRI reconstruction

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

Assessment of Data Consistency through Cascades of Independently Recurrent Inference Machines for fast and robust accelerated MRI reconstruction

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

Mustango: Toward Controllable Text-to-Music Generation

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

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.