Video Super-Resolution
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Video Super-Resolution is a computer vision task that aims to increase the resolution of a video sequence, typically from lower to higher resolutions. The goal is to generate high-resolution video frames from low-resolution input, improving the overall quality of the video.
<span style="color:grey; opacity: 0.6">( Image credit: Detail-revealing Deep Video Super-Resolution )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/cviaai/PSF-GAN-ESTIMATION
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/dalexanderch/CFD
https://github.com/deepak112/Keras-SRGAN
https://github.com/djsinghnegi/SRINImageEnhancemrntGAN
https://github.com/doantienthongbku/ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/dokyeongK/Pytorch_SRCNN
https://github.com/dokyeongK/Single-Image-Super-Resolution-Reimplemenation
https://github.com/drhdr-user/drhdr
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
https://github.com/eriklindernoren/PyTorch-GAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/fenghansen/ESRGAN-Keras
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/fengwang/subpixel_conv2d
https://github.com/ferseiti/reproducibility
https://github.com/final-0/Real-ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/final-0/Real-ESRGAN-bicubic
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/fourseaforfriend/waifu2x
https://github.com/george-gca/sr-pytorch-lightning
https://github.com/gongzix/neuroclips
Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models
https://github.com/gq-sonofgod/zoom-picture
https://github.com/gs18113/ESPCN-TensorFlow2
https://github.com/heartyguy/AI-AngryBird-Eagle-Wing
https://github.com/idealo/image-super-resolution
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/imatge-upc/3D-GAN-superresolution
https://github.com/isaaccorley/torchrs
https://github.com/itsuki8914/ESRGAN-TensorFlow
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/jaingaurav3/GAN-Hacks
https://github.com/jaivanti/Super-Resolution-using-ConvNet
https://github.com/jcao216/DAIN_Modified
https://github.com/jiangzhongkai/ifly-algorithm_challenge
https://github.com/jimmycv07/DiffIR2VR-Zero
Upscale-A-Video: Temporal-Consistent Diffusion Model for Real-World Video Super-Resolution
https://github.com/jixiaozhong/RealSR
https://github.com/jlanday/Language-Detection
https://github.com/jlanday/Model-Selection-for-Pion-Photoproduction
https://github.com/jlanday/Towards-the-Minimal-Spectrum-of-Excited-Baryons
https://github.com/jlanday/X-ray-Object-Classification
https://github.com/joezengcbs/mini_xgboost_from_scratch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.