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3D Object Super-Resolution

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3D object super-resolution is the task of up-sampling 3D objects.

<span style="color:grey; opacity: 0.6">( Image credit: Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation )</span>

코드

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

https://github.com/alles9fresser/Vanilla-GAN

Generative Adversarial Networks

https://github.com/allnightlight/ConditionalWassersteinAutoencoderPoweredBySinkhornDistance

Generative Adversarial Networks

https://github.com/alterzero/DBPN-Pytorch

Deep Back-Projection Networks For Super-Resolution

https://github.com/alterzero/RBPN-PyTorch

The 2018 PIRM Challenge on Perceptual Image Super-resolution

https://github.com/alterzero/STARnet

The 2018 PIRM Challenge on Perceptual Image Super-resolution

https://github.com/alvarobasi/eyeSRGAN

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

https://github.com/amanshenoy/image-super-resolution

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/amazingyyc/Brouhaha

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/amiq-consulting/image-upscaling-CNN

Accelerating the Super-Resolution Convolutional Neural Network

https://github.com/amogh7joshi/media-vision

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/amurthy1/dagan

Sampling Generative Networks

https://github.com/amzamzamzamz/nagadomi-waifu2x

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/anastassia-b/neural-algorithm-artistic-style

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/anchen1011/toflow

Video Enhancement with Task-Oriented Flow

https://github.com/andreacoppari/ELSR-torch

ELSR: Extreme Low-Power Super Resolution Network For Mobile Devices

https://github.com/andreamazzitelli/ProjectNN

Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model

https://github.com/andreas128/NTIRE21_Learning_SR_Space

Explorable Super Resolution

https://github.com/andreasfloros/IRN

Invertible Image Rescaling

https://github.com/andrerclaudio/channel_estimation

Deep Learning-Based Channel Estimation

https://github.com/andrewhproppe/phaseretrievalnns

Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections

https://github.com/anhkhoa039/Neural-Style-Transfer

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/animesh-007/Basic_GAN_Implementation

Generative Adversarial Networks

https://github.com/anjalipemmaraju/styletransfernetwork

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/ankanbhunia/Handwriting-Transformers

High-Resolution Image Synthesis with Latent Diffusion Models

https://github.com/anktplwl91/Image-Superresolution

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

https://github.com/anthonyzhou-1/pretraining_pdes

Masked Autoencoders are PDE Learners

https://github.com/anujdutt9/Artistic-Style-Transfer-using-Keras-Tensorflow

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/anujdutt9/ESPCN

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

https://github.com/anujtyagi2802/SRGAN

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

https://github.com/anushka-s/Image-restoration-using-deep-image-prior

Deep Image Prior

https://github.com/anushkayadav/Denoising_cifar10

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

https://github.com/ariel415el/Simple-SinGAN

SinGAN: Learning a Generative Model from a Single Natural Image

https://github.com/arjunarao619/SRCNN_Pytorch

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/arm-software/ml-restructurable-activation-networks

Collapsible Linear Blocks for Super-Efficient Super Resolution

https://github.com/arnonbruno/ganify

Generative Adversarial Networks

https://github.com/arpit2412/Generative-Adversarial-Network-/tree/master/GAN/MNIST_GAN/MNIST%20Easy

Generative Adversarial Networks

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