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followers: 40.0 following: 81.0 repos: 18.0 gists: 0.0

Name: House_Lee

Type: User

Company: IMAG, Nanjing University of Science and Technology

Bio: Ph.D. Candidate of IMAG, NJUST. Image Restoration

Location: Nanjing, China

Blog: house-leo.github.io

Hi, 👋 I'm House Lee (Hao Li)

😄 About Me: ⬇️

I’m currently a second-year Ph.D. candidate of IMAG (Nanjing University of Science and Technology), advised by Prof. Jinshan Pan.
I’m currently learning low-level image processing, especially image denoising and super resolution.

Please feel free to contact me via email or the following platform!

📫 Academic Service: ⬇️

Conference Reviewer
- ECCV 2022
- AAAI 2023, CVPR 2023, ICCV 2023
- AAAI 2024, CVPR 2024, ECCV 2024

House_Lee's Projects

autoapisecret

加密版，应用id/机密不再可见

awesome-image-denoising

Collect image denoising related papers, datasets, especially real-world image denoising.

basicsr2.0

Update BasicSR to support PyTorch2.0 DDP training

cfdvsr

Collaborative Feedback Discriminative Propagation for Video Super-Resolution

dnswin

Codes for our paper "DnSwin: Toward Real-World Denoising via Continuous Wavelet Sliding-Transformer" (KBS 2022)

glados-auto-checkin

GLADOS自动签到，多账号签到

glados-checkin

利用GitHub自带的Actions实现GLaDOS每天自动签到，并使用Server酱或pushPlus推送消息到微信

glados-signin

通过 GitHub Action 自动签到，每天延时一天，签到一定次数后奖励会变少

house-leo

house-leo.github.io

Hao Li's Personal Website

low-level-tools

Some useful scripts for my low-level projects

njustphdroad

从开题到离校——南京理工大学博士毕业之路

prrn

The testing code for our paper "Progressive Representation Re-Calibration Network for Lightweight Super-Resolution", Neurocomputing 2022

pytorch-cnn-visualizations

Pytorch implementation of convolutional neural network visualization techniques

realsr-ccl

Codes for “Criteria Comparative Learning for Real-scene Image Super-Resolution” (TCSVT 2022)

realsr-zero

RealSR-Zero dataset provided by our paper "Criteria Comparative Learning for Real-scene Image Super-Resolution"

rwsr-edl

Codes for "Real-World Image Super-Resolution by Exclusionary Dual-Learning" (TMM 2022)

sr_metrics_test

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