905 Repositories
Python self-supervised-landmarks Libraries
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training [Arxiv] VideoMAE: Masked Autoencoders are Data-Efficient Learne
[CVPR 2022] PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision (Oral)
PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision Kehong Gong*, Bingbing Li*, Jianfeng Zhang*, Ta
PyTorch implementation of U-TAE and PaPs for satellite image time series panoptic segmentation.
Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks (ICCV 2021) This repository is the official implem
Scribble-Supervised LiDAR Semantic Segmentation, CVPR 2022 (ORAL)
Scribble-Supervised LiDAR Semantic Segmentation Dataset and code release for the paper Scribble-Supervised LiDAR Semantic Segmentation, CVPR 2022 (ORA
Explorer is a Autonomous (self-hosted) Bittorrent Network Search Engine.
Explorer Explorer is a Autonomous (self-hosted) Bittorrent Network Search Engine. About The Project Screenshots Supported features Number Feature 1 DH
[CVPR'22] Weakly Supervised Semantic Segmentation by Pixel-to-Prototype Contrast
wseg Overview The Pytorch implementation of Weakly Supervised Semantic Segmentation by Pixel-to-Prototype Contrast. [arXiv] Though image-level weakly
A PyTorch implementation of Mugs proposed by our paper "Mugs: A Multi-Granular Self-Supervised Learning Framework".
Mugs: A Multi-Granular Self-Supervised Learning Framework This is a PyTorch implementation of Mugs proposed by our paper "Mugs: A Multi-Granular Self-
[cvpr22] Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation
PS-MT [cvpr22] Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation by Yuyuan Liu, Yu Tian, Yuanhong Chen, Fengbei Liu, Vasile
Official repository for the paper "Self-Supervised Models are Continual Learners" (CVPR 2022)
Self-Supervised Models are Continual Learners This is the official repository for the paper: Self-Supervised Models are Continual Learners Enrico Fini
FreeSOLO for unsupervised instance segmentation, CVPR 2022
FreeSOLO: Learning to Segment Objects without Annotations This project hosts the code for implementing the FreeSOLO algorithm for unsupervised instanc
A library built upon PyTorch for building embeddings on discrete event sequences using self-supervision
pytorch-lifestream a library built upon PyTorch for building embeddings on discrete event sequences using self-supervision. It can process terabyte-si
(CVPR 2022) A minimalistic mapless end-to-end stack for joint perception, prediction, planning and control for self driving.
LAV Learning from All Vehicles Dian Chen, Philipp Krähenbühl CVPR 2022 (also arXiV 2203.11934) This repo contains code for paper Learning from all veh
[CVPR 2022 Oral] Crafting Better Contrastive Views for Siamese Representation Learning
Crafting Better Contrastive Views for Siamese Representation Learning (CVPR 2022 Oral) 2022-03-29: The paper was selected as a CVPR 2022 Oral paper! 2
Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)
CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding (CVPR'22) Paper Link | Project Page Abstract : Manual an
torchlm is aims to build a high level pipeline for face landmarks detection, it supports training, evaluating, exporting, inference(Python/C++) and 100+ data augmentations
💎A high level pipeline for face landmarks detection, supports training, evaluating, exporting, inference and 100+ data augmentations, compatible with torchvision and albumentations, can easily install with pip.
Unsupervised phone and word segmentation using dynamic programming on self-supervised VQ features.
Unsupervised Phone and Word Segmentation using Vector-Quantized Neural Networks Overview Unsupervised phone and word segmentation on speech data is pe
Implementation of CaiT models in TensorFlow and ImageNet-1k checkpoints. Includes code for inference and fine-tuning.
CaiT-TF (Going deeper with Image Transformers) This repository provides TensorFlow / Keras implementations of different CaiT [1] variants from Touvron
Azure free vpn for students only! (Self hosted/No sketchy services/Fast and free)
Azpn-Azure-Free-VPN Azure free vpn for students only! (Self hosted/No sketchy services/Fast and free) This is an alternative secure way of accessing f
PyTorch implementation of "data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language" from Meta AI
data2vec-pytorch PyTorch implementation of "data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language" from Meta AI (F
(CVPR 2022) Pytorch implementation of "Self-supervised transformers for unsupervised object discovery using normalized cut"
(CVPR 2022) TokenCut Pytorch implementation of Tokencut: Self-supervised Transformers for Unsupervised Object Discovery using Normalized Cut Yangtao W
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology (LMRL Workshop, NeurIPS 2021)
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology Self-Supervised Vision Transformers Learn Visual Concepts in Histopatholog
Group R-CNN for Point-based Weakly Semi-supervised Object Detection (CVPR2022)
Group R-CNN for Point-based Weakly Semi-supervised Object Detection (CVPR2022) By Shilong Zhang*, Zhuoran Yu*, Liyang Liu*, Xinjiang Wang, Aojun Zhou,
Open source implementation of "A Self-Supervised Descriptor for Image Copy Detection" (SSCD).
A Self-Supervised Descriptor for Image Copy Detection (SSCD) This is the open-source codebase for "A Self-Supervised Descriptor for Image Copy Detecti
PromptDet: Expand Your Detector Vocabulary with Uncurated Images
PromptDet: Expand Your Detector Vocabulary with Uncurated Images Paper Website Introduction The goal of this work is to establish a scalable pipeline
SelfRemaster: SSL Speech Restoration
SelfRemaster: Self-Supervised Speech Restoration Official implementation of SelfRemaster: Self-Supervised Speech Restoration with Analysis-by-Synthesi
LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT
LightHuBERT LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT | Github | Huggingface | SUPER
Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic Segmentation (CVPR 2022)
CCAM (Unsupervised) Code repository for our paper "CCAM: Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localizati
Official implementation of "Watermarking Images in Self-Supervised Latent-Spaces"
🔍 Watermarking Images in Self-Supervised Latent-Spaces PyTorch implementation and pretrained models for the paper. For details, see Watermarking Imag
CVPR2022 paper "Dense Learning based Semi-Supervised Object Detection"
[CVPR2022] DSL: Dense Learning based Semi-Supervised Object Detection DSL is the first work on Anchor-Free detector for Semi-Supervised Object Detecti
Weakly Supervised Text-to-SQL Parsing through Question Decomposition
Weakly Supervised Text-to-SQL Parsing through Question Decomposition The official repository for the paper "Weakly Supervised Text-to-SQL Parsing thro
The code is for the paper "A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation"
SD-AANet The code is for the paper "A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation" [arxiv] Overview confi
The offcial repository for 'CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos', SIGIR2022
CharacterBERT-DR The offcial repository for CharacterBERT and Self-Teaching for Improving the Robustness of Dense Retrievers on Queries with Typos, Sh
Codes for SIGIR'22 Paper 'On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation'
OD-Rec Codes for SIGIR'22 Paper 'On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation' Paper, saved teacher models and Andro
RODD: A Self-Supervised Approach for Robust Out-of-Distribution Detection
RODD Official Implementation of 2022 CVPRW Paper RODD: A Self-Supervised Approach for Robust Out-of-Distribution Detection Introduction: Recent studie
Implementation of the Hybrid Perception Block and Dual-Pruned Self-Attention block from the ITTR paper for Image to Image Translation using Transformers
ITTR - Pytorch Implementation of the Hybrid Perception Block (HPB) and Dual-Pruned Self-Attention (DPSA) block from the ITTR paper for Image to Image
Code for ACL 2022 main conference paper "STEMM: Self-learning with Speech-text Manifold Mixup for Speech Translation".
STEMM: Self-learning with Speech-Text Manifold Mixup for Speech Translation This is a PyTorch implementation for the ACL 2022 main conference paper ST
This is an official implementation of the CVPR2022 paper "Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots".
Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots Blind2Unblind Citing Blind2Unblind @inproceedings{wang2022blind2unblind, tit
Simple Self-Bot for Discord
KeunoBot 🐼 -Simple Self-Bot for Discord KEUNOBOT 🐼 - Run KeunoBot : /* - Install KeunoBot - Extract it - Run setup.bat - Set token and prefi
Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"
Memory Efficient Attention Pytorch Implementation of a memory efficient multi-head attention as proposed in the paper, Self-attention Does Not Need O(
[CVPR 2022] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
Using Unreliable Pseudo Labels Official PyTorch implementation of Semi-Supervised Semantic Segmentation Using Unreliable Pseudo Labels, CVPR 2022. Ple
[CVPR 2022] Back To Reality: Weak-supervised 3D Object Detection with Shape-guided Label Enhancement
Back To Reality: Weak-supervised 3D Object Detection with Shape-guided Label Enhancement Announcement 🔥 We have not tested the code yet. We will fini
Self-driving car env with PPO algorithm from stable baseline3
Self-driving car with RL stable baseline3 Most of the project develop from https://github.com/GerardMaggiolino/Gym-Medium-Post Please check it out! Th
Tensorflow 1.13.X implementation for our NN paper: Wei Xia, Sen Wang, Ming Yang, Quanxue Gao, Jungong Han, Xinbo Gao: Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation. Neural Networks 145: 1-9 (2022)
Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation Simple implementation of our paper MVGC. The d
E2e music remastering system - End-to-end Music Remastering System Using Self-supervised and Adversarial Training
End-to-end Music Remastering System This repository includes source code and pre
Smart edu-autobooking - Johnson @ DMI-UNICT study room self-booking system
smart_edu-autobooking Sistema di autoprenotazione per l'aula studio Johnson@DMI-
Discord-selfbot - Very basic discord self bot
discord-selfbot Very basic discord self bot still being actively developed requi
SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING - The Facebook paper about fine tuning RoBERTa with contrastive loss
"# SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING" i
Code and Datasets from the paper "Self-supervised contrastive learning for volcanic unrest detection from InSAR data"
Code and Datasets from the paper "Self-supervised contrastive learning for volcanic unrest detection from InSAR data" You can download the pretrained
A Broad Study on the Transferability of Visual Representations with Contrastive Learning
A Broad Study on the Transferability of Visual Representations with Contrastive Learning This repository contains code for the paper: A Broad Study on
Learning Visual Words for Weakly-Supervised Semantic Segmentation
[IJCAI 2021] Learning Visual Words for Weakly-Supervised Semantic Segmentation Implementation of IJCAI 2021 paper Learning Visual Words for Weakly-Sup
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks
Code for CCA-SSG model proposed in the NeurIPS 2021 paper From Canonical Correlation Analysis to Self-supervised Graph Neural Networks.
Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices
Face-Mesh Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices. It employs machine learning
Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks
Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks This repository contains the code and data for the corresp
Implementation of SOMs (Self-Organizing Maps) with neighborhood-based map topologies.
py-self-organizing-maps Simple implementation of self-organizing maps (SOMs) A SOM is an unsupervised method for learning a mapping from a discrete ne
Supervised Contrastive Learning for Product Matching
Contrastive Product Matching This repository contains the code and data download links to reproduce the experiments of the paper "Supervised Contrasti
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification
Byzantine-robust decentralized learning via self-centered clipping
Byzantine-robust decentralized learning via self-centered clipping In this paper, we study the challenging task of Byzantine-robust decentralized trai
Python package for concise, transparent, and accurate predictive modeling
Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern
The mini-AlphaStar (mini-AS, or mAS) - mini-scale version (non-official) of the AlphaStar (AS)
A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.
Simple implementation of Self Organizing Maps (SOMs) with rectangular and hexagonal grid topologies
py-self-organizing-map Simple implementation of Self Organizing Maps (SOMs) with rectangular and hexagonal grid topologies. A SOM is a simple unsuperv
Implementation of the method described in the Speech Resynthesis from Discrete Disentangled Self-Supervised Representations.
Speech Resynthesis from Discrete Disentangled Self-Supervised Representations Implementation of the method described in the Speech Resynthesis from Di
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open
Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification
Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification Introduction. This package includes the pyth
Ssl-tool - A simple interactive CLI wrapper around openssl to make creation and installation of self-signed certs easy
What's this? A simple interactive CLI wrapper around openssl to make self-signin
This project proposes a camera vision based cursor control system, using hand moment captured from a webcam through a landmarks of hand by using Mideapipe module
This project proposes a camera vision based cursor control system, using hand moment captured from a webcam through a landmarks of hand by using Mideapipe module
Convolutional neural network that analyzes self-generated images in a variety of languages to find etymological similarities
This project is a convolutional neural network (CNN) that analyzes self-generated images in a variety of languages to find etymological similarities. Specifically, the goal is to prove that computer vision can be used to identify cognates known to exist, and perhaps lead linguists to evidence of unknown cognates.
Mae segmentation - Reproduction of semantic segmentation using masked autoencoder (mae)
ADE20k Semantic segmentation with MAE Getting started Install the mmsegmentation
Real-time domain adaptation for semantic segmentation
Advanced-Machine-Learning This repository contains the code for the project Real
PyTorch implementation of DirectCLR from paper Understanding Dimensional Collapse in Contrastive Self-supervised Learning
DirectCLR DirectCLR is a simple contrastive learning model for visual representation learning. It does not require a trainable projector as SimCLR. It
Supervised Sliding Window Smoothing Loss Function Based on MS-TCN for Video Segmentation
SSWS-loss_function_based_on_MS-TCN Supervised Sliding Window Smoothing Loss Function Based on MS-TCN for Video Segmentation Supervised Sliding Window
Pytorch Implementation of Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations
NANSY: Unofficial Pytorch Implementation of Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations Notice Papers' D
Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive losses
Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss
CAST: Character labeling in Animation using Self-supervision by Tracking
CAST: Character labeling in Animation using Self-supervision by Tracking (Published as a conference paper at EuroGraphics 2022) Note: The CAST paper c
Using Self-Supervised Pretext Tasks for Active Learning - Official Pytorch Implementation
Using Self-Supervised Pretext Tasks for Active Learning - Official Pytorch Implementation Experiment Setting: CIFAR10 (downloaded and saved in ./DATA
Self-Supervised Deep Blind Video Super-Resolution
Self-Blind-VSR Paper | Discussion Self-Supervised Deep Blind Video Super-Resolution By Haoran Bai and Jinshan Pan Abstract Existing deep learning-base
PyTorch implementation for the paper Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime
Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime Created by Prarthana Bhattacharyya. Disclaimer: This is n
Learning to Predict Gradients for Semi-Supervised Continual Learning
Learning to Predict Gradients for Semi-Supervised Continual Learning Code for project: "Learning to Predict Gradients for Semi-Supervised Continual Le
Code for project: "Learning to Minimize Remainder in Supervised Learning".
Learning to Minimize Remainder in Supervised Learning Code for project: "Learning to Minimize Remainder in Supervised Learning". Requirements and Envi
Official code of "Mitigating the Mutual Error Amplification for Semi-Supervised Object Detection"
CrossTeaching-SSOD 0. Introduction Official code of "Mitigating the Mutual Error Amplification for Semi-Supervised Object Detection" This repo include
This tool is created by Shahzain and is one of the best self bots out there!
Shahzain SelfBot This tool is created by Shahzain and is one of the best self bots out there! Features Token Destroyer! Server Nuker(50-100 Bans Per S
Innocent-Bot - A Discord client self-bot for destroying, nuking and causing mischief in servers
Innocent-bot A Discord client self-bot for destroying, nuking and causing mischi
SAS: Self-Augmentation Strategy for Language Model Pre-training
SAS: Self-Augmentation Strategy for Language Model Pre-training This repository
Revisiting Weakly Supervised Pre-Training of Visual Perception Models
SWAG: Supervised Weakly from hashtAGs This repository contains SWAG models from the paper Revisiting Weakly Supervised Pre-Training of Visual Percepti
Cycle Self-Training for Domain Adaptation (NeurIPS 2021)
CST Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021) Prerequisites torch=1.7.0 torchvision qpsolvers numpy prettytable tqd
Self-supervised learning (SSL) is a method of machine learning
Self-supervised learning (SSL) is a method of machine learning. It learns from unlabeled sample data. It can be regarded as an intermediate form between supervised and unsupervised learning.
My self-hosting infrastructure, fully automated from empty disk to operating services
Khue's Homelab Current status: ALPHA This project utilizes Infrastructure as Code to automate provisioning, operating, and updating self-hosted servic
This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"
ICCV Workshop 2021 VTGAN This code is for our paper "VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers"
Source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree.
self-driving-car In this repository I will share the source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree. Hope this might
DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency
[CVPR19] DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency (Oral paper) Authors: Kuang-Jui Hsu, Yen-Yu Lin, Yung-Yu Chuang PDF:
MODSKIN-LOLPRO-updater: The mod is fkn 10y old and has'nt a self-updater
The mod is fkn 10y old and has'nt a self-updater. To use it just run the exec, wait some seconds, and it will run the new modsk
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images Histological Image Segmentation This
BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python
BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python. Some of the algorithms included are mor
PyToch implementation of A Novel Self-supervised Learning Task Designed for Anomaly Segmentation
Self-Supervised Anomaly Segmentation Intorduction This is a PyToch implementation of A Novel Self-supervised Learning Task Designed for Anomaly Segmen
Transformer in Vision
Transformer-in-Vision Recent Transformer-based CV and related works. Welcome to comment/contribute! Keep updated. Resource SCENIC: A JAX Library for C
A curated list of efficient attention modules
awesome-fast-attention A curated list of efficient attention modules
Meta Self-learning for Multi-Source Domain Adaptation: A Benchmark
Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark Project | Arxiv | YouTube | | Abstract In recent years, deep learning-based methods
cl;asification problem using classification models in supervised learning
wine-quality-predition---classification cl;asification problem using classification models in supervised learning Wine Quality Prediction Analysis - C
Fuzzware is a project for automated, self-configuring fuzzing of firmware images
Fuzzware Fuzzware is a project for automated, self-configuring fuzzing of firmware images. The idea of this project is to configure the memory ranges
A complete, self-contained example for training ImageNet at state-of-the-art speed with FFCV
ffcv ImageNet Training A minimal, single-file PyTorch ImageNet training script designed for hackability. Run train_imagenet.py to get... ...high accur