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Hi there 👋

😜 I'm currently a student in Wuhan University. My major is computer science. And recently I'm trying to do some research in computer vision. Now I'm working on super-resolution problems. Besides, I am also able to do sth in software development.

(●'◡'●)Hope I can give some useful output in my github account!

Sicheng Hu's Projects

basicsr icon basicsr

Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, etc. Also support StyleGAN2, DFDNet.

brcn icon brcn

A unofficial implementation of paper method that 'Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution'

bsrgan icon bsrgan

Designing a Practical Degradation Model for Deep Blind Image Super-Resolution (PyTorch) - We released the testing code!

dpir icon dpir

Plug-and-Play Image Restoration with Deep Denoiser Prior (IEEE TPAMI 2021) (PyTorch)

dpsr icon dpsr

Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels (CVPR, 2019) (PyTorch)

ecl icon ecl

The code of ECL: Exclusive Curriculum Learning for Video Super-Resolution.

edvr icon edvr

Winning Solution in NTIRE19 Challenges on Video Restoration and Enhancement (CVPR19 Workshops) - Video Restoration with Enhanced Deformable Convolutional Networks. EDVR has been merged into BasicSR and this repo is a mirror of BasicSR.

esrgan icon esrgan

ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.

gfn icon gfn

Gated Fusion Network for Joint Image Deblurring and Super-Resolution(BMVC 2018 Oral)

imdn icon imdn

Lightweight Image Super-Resolution with Information Multi-distillation Network (ACM MM 2019, Winner Award of ICCVW AIM 2019 Constrained SR Track1&Track2)

kair icon kair

Image Restoration Toolbox (PyTorch). Training and testing codes for USRNet, DnCNN, FFDNet, SRMD, DPSR, ESRGAN

meta-sr-pytorch icon meta-sr-pytorch

Meta-SR: A Magnification-Arbitrary Network for Super-Resolution (CVPR2019)

ml_demo icon ml_demo

一些机器学习算法的demo。普通最小二乘法,决策树(Iris鸢尾花数据集),KNN(mnist手写数字数据集),朴素贝叶斯分类西瓜数据集,trec06c数据集垃圾邮件分类(spam),逻辑斯蒂回归,随机梯度下降SGD与全梯度下降的对比,mnist中8和9的二分类,泰坦尼克号数据集。

multi-mono-sf icon multi-mono-sf

Self-Supervised Multi-Frame Monocular Scene Flow (CVPR 2021)

pfnl icon pfnl

Progressive Fusion Video Super-Resolution Network via Exploiting Non-Local Spatio-Temporal Correlations

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