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/Oishani/Machine-Learning-Projects

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/One-sixth/pixelshuffle_invert_pytorch

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

https://github.com/Pea-Shooter/ADNet

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

https://github.com/Pulkitdzrt/ML-Image-Super-Resolution

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/RezisEwig/esrgan

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/SJHNJU/VDSR

Accurate Image Super-Resolution Using Very Deep Convolutional Networks

https://github.com/Shritesh99/100DaysofMLCodeChallenge

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/Shritesh99/Image_Super_Resolution

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/SimoneDutto/EDSR

Deep Back-Projection Networks For Super-Resolution

https://github.com/TahmasbiM/Example

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

https://github.com/TanakitInt/SRCNN-anime

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/TomokiKomiya/SRGAN-keras

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

https://github.com/WarrenGreen/srcnn

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/Weifeng73/Zero-Shot-Super-resolution

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/XPixelGroup/BasicSR

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

https://github.com/XiuyuLiu/Application-of-Deep-Learning-models-in-Single-Image-Super-Resolution

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/YanyingZH/srgan-esrgan-pytorch

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/YapengTian/TDAN-VSR-CVPR-2020

TDAN: Temporally Deformable Alignment Network for Video Super-Resolution

https://github.com/YapengTian/TDAN_VSR

TDAN: Temporally Deformable Alignment Network for Video Super-Resolution

https://github.com/YeongHyeon/Super-Resolution_CNN

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/YeongHyeon/Super-Resolution_CNN-PyTorch

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/Yuki0114/UndergraduateThesis_SRCNN_keras

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/YvanG/VQGAN-CLIP

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/Zhangyanbo/iResNetLab

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

https://github.com/ZhaoHengrun/EDVR

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

https://github.com/ZiqiaoPeng/EmoTalk

EmoTalk: Speech-Driven Emotional Disentanglement for 3D Face Animation

https://github.com/aba450/Super-Resolution

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/abdulwaheedsoudagar/SR-CNN

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/adbobes/VideoSuperResolution

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

https://github.com/agnesdeng/mixgb

XGBoost: A Scalable Tree Boosting System

https://github.com/ai-forever/kandinskyvideo

Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models

https://github.com/akashpalrecha/deblurring-pipeline

Deep Back-Projection Networks For Super-Resolution

https://github.com/akashpalrecha/superres-deformable

Deep Back-Projection Networks For Super-Resolution

https://github.com/alexjc/neural-enhance

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

https://github.com/alililia/ascend_ESRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/allenai/satlas-super-resolution

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

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