mrluin

seemoredetails

Repository for our paper "See More Details: Efficient Image Super-Resolution by Experts Mining"

DaAIR

GitHub repository for our project "Efficient Degradation-aware Any Image Restoration"

mmengine

OpenMMLab Foundational Library for Training Deep Learning Models

AdaIR

AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation

Awesome-All-In-One-Image-Restoration

This is a summary of research on All-In-One Image/Video Restoration. There may be omissions. If anything is missing please get in touch with us. Our emails: liboyun.gm@gmail.com; gouyuanbiao@gmail.com; haiyuzhao.gm@gmail.com; wangwenxin.gm@gmail.com

TGSR

NeurIPS 2023 - Real-world super-resolution as multi-task learning

Depth-Anything

[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation

cvbase

Utils for computer vision research.

CDFormer

RepRFN

Reparameterized Residual Feature Network For Lightweight Image Super-Resolution

LRSRN

simple_real_time_super_resolution

RepVGG

RepVGG: Making VGG-style ConvNets Great Again

ml-mobileone

This repository contains the official implementation of the research paper, "An Improved One millisecond Mobile Backbone".

conformal-prediction

Lightweight, useful implementation of conformal prediction on real data.

SelfDZSR_PlusPlus

[TPAMI 2024] Self-Supervised Learning for Real-World Super-Resolution from Dual and Multiple Zoomed Observations

Angular-Penalty-Softmax-Losses-Pytorch

Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

AMSoftmax

A simple yet effective loss function for face verification.

pyclustering

pyclustering is a Python, C++ data mining library.

Shift-Net

A Simple Baseline for Video Restoration with Grouped Spatial-temporal Shift

MetaCLIP

ICLR2024 Spotlight: curation/training code, metadata, distribution and pre-trained models for MetaCLIP; CVPR 2024: MoDE: CLIP Data Experts via Clustering

kmeans_pytorch

kmeans using PyTorch

AdaFM

CVPR2019 (oral) Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers (AdaFM). PyTorch implementation

TextPromptIR

Textual Prompt Guided Image Restoration

mixture-of-experts

PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538

Automold--Road-Augmentation-Library

This library augments road images to introduce various real world scenarios that pose challenges for training neural networks of Autonomous vehicles. Automold is created to train CNNs in specific weather and road conditions.

Simple-Align

https://arxiv.org/abs/2402.18929

InstructIR

InstructIR: High-Quality Image Restoration Following Human Instructions https://huggingface.co/spaces/marcosv/InstructIR

Bayesian-Neural-Networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

HeavyRainRemoval

An implementation of paper "Heavy Rain Image Restoration: Integrating Physics Model and Conditional Adversarial Learning" (CVPR19)

MiOIR

Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy