Python MixCo-Mixup-Contrast Resources

wseg Overview The Pytorch implementation of Weakly Supervised Semantic Segmentation by Pixel-to-Prototype Contrast. [arXiv] Though image-level weakly

STEMM: Self-learning with Speech-Text Manifold Mixup for Speech Translation This is a PyTorch implementation for the ACL 2022 main conference paper ST

A simple code to process images using contrast limited adaptive histogram equalization. Image processing is becoming a major part of data processig.

CECED-Canny-Edge-Contrast-Enhanced-Detection A simple code to perform canny edge contrast detection on images. A simple code to process images using c

MoCoPnet: Exploring Local Motion and Contrast Priors for Infrared Small Target Super-Resolution Pytorch implementation of local motion and contrast pr

Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data This is the official PyTorch implementation of the SeCo paper: @articl

OpenSelfSup News Downstream tasks now support more methods(Mask RCNN-FPN, RetinaNet, Keypoints RCNN) and more datasets(Cityscapes). 'GaussianBlur' is

Subg-Con Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning (Jiao et al., ICDM 2020): https://arxiv.org/abs/2009.10273 Over

CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we

MoCo: Momentum Contrast for Unsupervised Visual Representation Learning This is a PyTorch implementation of the MoCo paper: @Article{he2019moco, aut

CoG-BART Contrast and Generation Make BART a Good Dialogue Emotion Recognizer Quick Start: To run the model on test sets of four datasets, Download th

Contrast and Mix (CoMix) The repository contains the codes for the paper Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Backgroun

Manifold Mixup Unofficial implementation of ManifoldMixup (Proceedings of ICML 19) for fast.ai (V2) based on Shivam Saboo's pytorch implementation of

MixRNet(Using mixup as regularization and tuning hyper-parameters for ResNets) Using mixup data augmentation as reguliraztion and tuning the hyper par

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021) PyTorch implementation of SnapMix | paper Method Overview Cite

CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we

The Code for MM2021 paper "Multi-Level Counterfactual Contrast for Visual Commonsense Reasoning" Setting up and using the repo Get the dataset. Follow

Core-tuning This repository is the official implementation of ``Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regular

MIST Training MIST TRAIN_FILE=/your/path/to/train.json VALID_FILE=/your/path/to/valid.json OUTPUT_DIR=/your/path/to/save_checkpoints CACHE_DIR=/your/p

Unofficial implementation: MoCo: Momentum Contrast for Unsupervised Visual Representation Learning (Paper) InsDis: Unsupervised Feature Learning via N

Mixup-Data-Dependency Code associated with the paper "Towards Understanding the Data Dependency of Mixup-style Training". Running Alternating Line Exp

PyPhotoshop Python implementation of image filters Use Python to adjust brightness and contrast, add blur, and detect edges! Follow along tutorial: ht

CyTran: Cycle-Consistent Transformers for Non-Contrast to Contrast CT Translation We propose a novel approach to translate unpaired contrast computed

SANet Exploring Separable Attention for Multi-Contrast MR Image Super-Resolution Dependencies numpy==1.18.5 scikit_image==0.16.2 torchvision==0.8.1 to

Mixup: Beyond Empirical Risk Minimization in PyTorch This is an unofficial PyTorch implementation of mixup: Beyond Empirical Risk Minimization. The co

How to Reproduce our Results This repository contains PyTorch implementation code for the paper MixCo: Mix-up Contrastive Learning for Visual Represen

LADA This repo contains codes for the following paper: Jiaao Chen*, Zhenghui Wang*, Ran Tian, Zichao Yang, Diyi Yang: Local Additivity Based Data Augm

Self-Supervised Learning for Domain Adaptation on Point-Clouds Introduction Self-supervised learning (SSL) allows to learn useful representations from

ReCo - Regional Contrast This repository contains the source code of ReCo and baselines from the paper, Bootstrapping Semantic Segmentation with Regio

Contrast to Divide: self-supervised pre-training for learning with noisy labels This is an official implementation of "Contrast to Divide: self-superv

Fair Mixup: Fairness via Interpolation Training classifiers under fairness constraints such as group fairness, regularizes the disparities of predicti

imgaug This python library helps you with augmenting images for your machine learning projects. It converts a set of input images into a new, much lar

Exploring Cross-Image Pixel Contrast for Semantic Segmentation Exploring Cross-Image Pixel Contrast for Semantic Segmentation, Wenguan Wang, Tianfei Z