Papers with Code 아카이브

3D Face Animation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

1

평가표

3

보존된 평가 기록

12

코드

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

https://github.com/07Agarg/Image-Resolution-Enhancement-SRCNN

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/1082-datascience/finalproject-finalproject-1082ds_group3

XGBoost: A Scalable Tree Boosting System

https://github.com/15517965908/keras-DBPN

Deep Back-Projection Networks For Super-Resolution

https://github.com/20151001860/Real_ESRGAN_paddle

Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

https://github.com/2023-MindSpore-1/ms-code-210/tree/main/DBPN

Deep Back-Projection Networks For Super-Resolution

https://github.com/2023-MindSpore-1/ms-code-213/tree/main/ESRGAN

Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

https://github.com/2023-MindSpore-1/ms-code-216/tree/main/rbpn

Recurrent Back-Projection Network for Video Super-Resolution

https://github.com/2023-MindSpore-4/Code11/tree/main/SRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/2023-MindSpore-4/Code7/tree/main/SRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/2023-MindSpore-4/Code7/tree/main/srcnn

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/360jinrong/GBST

XGBoost: A Scalable Tree Boosting System

https://github.com/545641826/espcn

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

https://github.com/Aanisha/SuperResolution

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/AbhinayReddyYarva/SuperResolution

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/Alioth2000/RASVSR

https://github.com/Amritha16/ImageResolutionEnhancement

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/AniketVashishtha/SUPER_RESOLUTION_DL

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/AnjanaGJoseph/Super-Resolution-GAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/Araxeus/PNG-Upscale

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

https://github.com/Automunge/AutoMunge

XGBoost: A Scalable Tree Boosting System

https://github.com/BIOINSu/LGFN

https://github.com/BearNinja123/esrGAN_vBearNinja123

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/Coldog2333/pytoflow

Video Enhancement with Task-Oriented Flow

https://github.com/CorentinMAG/SRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/Dictator890/ESRGAN-Android-Demo

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/DwightFoster/Pytorch-TecoGan

Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation

https://github.com/Feynman1999/MgeEditing

Video Super-Resolution with Recurrent Structure-Detail Network

https://github.com/Feynman1999/basicVSR_mge

BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

https://github.com/Fickle519/stockforecastingmodelbasedon_XGboost

XGBoost: A Scalable Tree Boosting System

https://github.com/FirstPotatoMan/TensorflowJS_ESRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/Fivefold/SRCNN

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/Fuhui-Chen/TecoGAN

Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation

https://github.com/GitHubXlong/TecoGAN

Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation

https://github.com/Gowti-AiboT/GAN-based-SISR-Keras

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/GuillaumeDufau/Image-super-resolution-vdsr

Accurate Image Super-Resolution Using Very Deep Convolutional Networks

https://github.com/HERMINDERSINGH1234/ML_Extra_Resolution_Increases

Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation

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