Python Supervised-autoencoder Resources

UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning This is the official PyTorch implementation for UniMoCo pape

Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning This is the PyTorch companion code for the paper: A

SASSnet Code for paper: Shape-aware Semi-supervised 3D Semantic Segmentation for Medical Images(MICCAI 2020) Our code is origin from UA-MT You can fin

Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation This paper has been accepted and early accessed

Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation (CVPR 2021, official Pytorch implementatio

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc

News March 3: v0.9.97 has various bug fixes and improvements: Bug fixes for NTXentLoss Efficiency improvement for AccuracyCalculator, by using torch i

CoMatch: Semi-supervised Learning with Contrastive Graph Regularization (Salesforce Research) This is a PyTorch implementation of the CoMatch paper [B

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

Diverse Image Captioning with Context-Object Split Latent Spaces This repository is the PyTorch implementation of the paper: Diverse Image Captioning

BossNAS This repository contains PyTorch evaluation code, retraining code and pretrained models of our paper: BossNAS: Exploring Hybrid CNN-transforme

Hierarchical Pretraining: Research Repository This is a research repository for reproducing the results from the project "Self-supervised pretraining

STN-OCR: A single Neural Network for Text Detection and Text Recognition This repository contains the code for the paper: STN-OCR: A single Neural Net

SEE: Towards Semi-Supervised End-to-End Scene Text Recognition Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text

Scene-Text-Detection-with-SPCNET Unofficial repository for [Scene Text Detection with Supervised Pyramid Context Network][https://arxiv.org/abs/1811.0

SuperGAT Official implementation of Self-supervised Graph Attention Networks (SuperGAT). This model is presented at How to Find Your Friendly Neighbor

TBE The source code for our paper "Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Le

Evaluation, Training, Demo, and Inference of DeFMO DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021) Denys Rozumnyi, Martin R. O

barlowtwins PyTorch Implementation of Barlow Twins paper: Barlow Twins: Self-Supervised Learning via Redundancy Reduction This is currently a work in

ASEGAN: Speech Enhancement Generative Adversarial Network Based on Asymmetric AutoEncoder 中文版简介 Readme with English Version 介绍 基于SEGAN模型的改进版本，使用自主设计的非

A supervised domain-agnostic framework that allows for probabilistic modelling, namely the prediction of probability distributions for individual data

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc

Dense Contrastive Learning for Self-Supervised Visual Pre-Training This project hosts the code for implementing the DenseCL algorithm for se

Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals This repo contains the Pytorch implementation of our paper: Unsupervised Seman

hope-autonomous-driving Autonomous Driving project for Euro Truck Simulator 2 Video: How is it working ? In this video, the program processes the imag

Puzzle-CAM The official implementation of "Puzzle-CAM: Improved localization via matching partial and full features".

The Great Autoencoder Bake Off The companion repository to a post on my blog. It contains all you need to reproduce the results. Features Currently fe

Unbiased Teacher for Semi-Supervised Object Detection This is the PyTorch implementation of our paper: Unbiased Teacher for Semi-Supervised Object Detection

Weakly Supervised Learning of Rigid 3D Scene Flow This repository provides code and data to train and evaluate a weakly supervised method for rigid 3D

This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.

FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning This is the PyTorch implementation of our paper: FeatMatch: Feature-Based Augmentat

DALL-E in Mesh-Tensorflow [WIP] Open-AI's DALL-E in Mesh-Tensorflow. If this is similarly efficient to GPT-Neo, this repo should be able to train mode

SupCon-Framework The repo is an implementation of Supervised Contrastive Learning. It's based on another implementation, but with several differencies

◥ Curriculum Labeling ◣ Revisiting Pseudo-Labeling for Semi-Supervised Learning Paola Cascante-Bonilla, Fuwen Tan, Yanjun Qi, Vicente Ordonez. In the

Context Matters: Graph-based Self-supervised Representation Learning for Medical Images Official PyTorch implementation for paper Context Matters: Gra

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch Website • Installation • Main

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2020 Links Doc

Python Outlier Detection (PyOD) Deployment & Documentation & Stats Build Status & Coverage & Maintainability & License PyOD is a comprehensive and sca

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

Lightly is a computer vision framework for self-supervised learning. We, at Lightly, are passionate engineers who want to make deep learning more effi