715 Repositories
Python unsupervised-accuracy-estimation Libraries
Labels4Free: Unsupervised Segmentation using StyleGAN
Labels4Free: Unsupervised Segmentation using StyleGAN ICCV 2021 Figure: Some segmentation masks predicted by Labels4Free Framework on real and synthet
Code for "Unsupervised Source Separation via Bayesian inference in the latent domain"
LQVAE-separation Code for "Unsupervised Source Separation via Bayesian inference in the latent domain" Paper Samples GT Compressed Separated Drums GT
Lbl2Vec learns jointly embedded label, document and word vectors to retrieve documents with predefined topics from an unlabeled document corpus.
Lbl2Vec Lbl2Vec is an algorithm for unsupervised document classification and unsupervised document retrieval. It automatically generates jointly embed
Face uncertainty quantification or estimation using PyTorch.
Face-uncertainty-pytorch This is a demo code of face uncertainty quantification or estimation using PyTorch. The uncertainty of face recognition is af
Weight estimation in CT by multi atlas techniques
maweight A Python package for multi-atlas based weight estimation for CT images, including segmentation by registration, feature extraction and model
R-package accompanying the paper "Dynamic Factor Model for Functional Time Series: Identification, Estimation, and Prediction"
dffm The goal of dffm is to provide functionality to apply the methods developed in the paper “Dynamic Factor Model for Functional Time Series: Identi
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
Optimal Camera Position for a Practical Application of Gaze Estimation on Edge Devices,
Optimal Camera Position for a Practical Application of Gaze Estimation on Edge Devices, Linh Van Ma, Tin Trung Tran, Moongu Jeon, ICAIIC 2022 (The 4th
A general framework for inferring CNNs efficiently. Reduce the inference latency of MobileNet-V3 by 1.3x on an iPhone XS Max without sacrificing accuracy.
GFNet-Pytorch (NeurIPS 2020) This repo contains the official code and pre-trained models for the glance and focus network (GFNet). Glance and Focus: a
Towards Boosting the Accuracy of Non-Latin Scene Text Recognition
Convolutional Recurrent Neural Network + CTCLoss | STAR-Net Code for paper "Towards Boosting the Accuracy of Non-Latin Scene Text Recognition" Depende
Official PyTorch implementation of "The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation" (ICCV 21).
CenterGroup This the official implementation of our ICCV 2021 paper The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person P
Transfer Learning for Pose Estimation of Illustrated Characters
bizarre-pose-estimator Transfer Learning for Pose Estimation of Illustrated Characters Shuhong Chen *, Matthias Zwicker * WACV2022 [arxiv] [video] [po
Algorithms for outlier, adversarial and drift detection
Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline d
(JMLR' 19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Python Outlier Detection (PyOD) Deployment & Documentation & Stats & License PyOD is a comprehensive and scalable Python toolkit for detecting outlyin
Python package for dynamic system estimation of time series
PyDSE Toolset for Dynamic System Estimation for time series inspired by DSE. It is in a beta state and only includes ARMA models right now. Documentat
FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks
FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
CheckList This repository contains code for testing NLP Models as described in the following paper: Beyond Accuracy: Behavioral Testing of NLP models
Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation (ICLR 2020)
U-GAT-IT — Official TensorFlow Implementation (ICLR 2020) : Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization fo
Anomaly detection related books, papers, videos, and toolboxes
Anomaly Detection Learning Resources Outlier Detection (also known as Anomaly Detection) is an exciting yet challenging field, which aims to identify
Official code for the ICCV 2021 paper "DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders"
DECA Official code for the ICCV 2021 paper "DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders". All the code is writte
Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21
Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose
HandFoldingNet ✌️ : A 3D Hand Pose Estimation Network Using Multiscale-Feature Guided Folding of a 2D Hand Skeleton
HandFoldingNet ✌️ : A 3D Hand Pose Estimation Network Using Multiscale-Feature Guided Folding of a 2D Hand Skeleton Wencan Cheng, Jae Hyun Park, Jong
Python3 / PyTorch implementation of the following paper: Fine-grained Semantics-aware Representation Enhancement for Self-supervisedMonocular Depth Estimation. ICCV 2021 (oral)
FSRE-Depth This is a Python3 / PyTorch implementation of FSRE-Depth, as described in the following paper: Fine-grained Semantics-aware Representation
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data This is the official PyTorch implementation of the SeCo paper: @articl
deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and different optimization choices
deep_nn_model_with_only_python_100%_test_accuracy deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and differen
NNR conformation conditional and global probabilities estimation and analysis in peptides or proteins fragments
NNR and global probabilities estimation and analysis in peptides or protein fragments This module calculates global and NNR conformation dependent pro
An interactive DNN Model deployed on web that predicts the chance of heart failure for a patient with an accuracy of 98%
Heart Failure Predictor About A Web UI deployed Dense Neural Network Model Made using Tensorflow that predicts whether the patient is healthy or has c
K-Means Clustering and Hierarchical Clustering Unsupervised Learning Solution in Python3.
Unsupervised Learning - K-Means Clustering and Hierarchical Clustering - The Heritage Foundation's Economic Freedom Index Analysis 2019 - By David Sal
Histology images query (unsupervised)
110-1-NTU-DBME5028-Histology-images-query Final Project: Histology images query (unsupervised) Kaggle: https://www.kaggle.com/c/histology-images-query
Machine learning library for fast and efficient Gaussian mixture models
This repository contains code which implements the Stochastic Gaussian Mixture Model (S-GMM) for event-based datasets Dependencies CMake Premake4 Blaz
Defocus Map Estimation and Deblurring from a Single Dual-Pixel Image
Defocus Map Estimation and Deblurring from a Single Dual-Pixel Image This repository is an implementation of the method described in the following pap
Rethinking the Truly Unsupervised Image-to-Image Translation - Official PyTorch Implementation (ICCV 2021)
Rethinking the Truly Unsupervised Image-to-Image Translation (ICCV 2021) Each image is generated with the source image in the left and the average sty
AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation
AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation AniGAN: Style-Guided Generative Adversarial Networks for U
IEGAN — Official PyTorch Implementation Independent Encoder for Deep Hierarchical Unsupervised Image-to-Image Translation
IEGAN — Official PyTorch Implementation Independent Encoder for Deep Hierarchical Unsupervised Image-to-Image Translation Independent Encoder for Deep
NICE-GAN — Official PyTorch Implementation Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation
NICE-GAN-pytorch - Official PyTorch implementation of NICE-GAN: Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation
MT-GAN-PyTorch - PyTorch Implementation of Learning to Transfer: Unsupervised Domain Translation via Meta-Learning
MT-GAN-PyTorch PyTorch Implementation of AAAI-2020 Paper "Learning to Transfer: Unsupervised Domain Translation via Meta-Learning" Dependency: Python
UI2I via StyleGAN2 - Unsupervised image-to-image translation method via pre-trained StyleGAN2 network
We proposed an unsupervised image-to-image translation method via pre-trained StyleGAN2 network. paper: Unsupervised Image-to-Image Translation via Pr
ZUNIT - Toward Zero-Shot Unsupervised Image-to-Image Translation
ZUNIT Dependencies you can install all the dependencies by pip install -r requirements.txt Datasets Download CUB dataset. Unzip the birds.zip at ./da
Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
U-GAT-IT — Official PyTorch Implementation : Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Imag
TensorFlow Implementation of Unsupervised Cross-Domain Image Generation
Domain Transfer Network (DTN) TensorFlow implementation of Unsupervised Cross-Domain Image Generation. Requirements Python 2.7 TensorFlow 0.12 Pickle
DualGAN-tensorflow: tensorflow implementation of DualGAN
ICCV paper of DualGAN DualGAN: unsupervised dual learning for image-to-image translation please cite the paper, if the codes has been used for your re
Unsupervised captioning - Code for Unsupervised Image Captioning
Unsupervised Image Captioning by Yang Feng, Lin Ma, Wei Liu, and Jiebo Luo Introduction Most image captioning models are trained using paired image-se
[3DV 2021] Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation
Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation This is the official implementation for the method described in Ch
SimpleDepthEstimation - An unified codebase for NN-based monocular depth estimation methods
SimpleDepthEstimation Introduction This is an unified codebase for NN-based monocular depth estimation methods, the framework is based on detectron2 (
Pseudo lidar - (CVPR 2019) Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving This paper has been accpeted by Conference o
Keras Realtime Multi-Person Pose Estimation - Keras version of Realtime Multi-Person Pose Estimation project
This repository has become incompatible with the latest and recommended version of Tensorflow 2.0 Instead of refactoring this code painfully, I create
Captcha-tensorflow - Image Captcha Solving Using TensorFlow and CNN Model. Accuracy 90%+
Captcha Solving Using TensorFlow Introduction Solve captcha using TensorFlow. Learn CNN and TensorFlow by a practical project. Follow the steps, run t
VQMIVC - Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion
VQMIVC: Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion (Interspeech
Python implementation of "Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation"
MIPNet: Multi-Instance Pose Networks This repository is the official pytorch python implementation of "Multi-Instance Pose Networks: Rethinking Top-Do
The official MegEngine implementation of the ICCV 2021 paper: GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning
[ICCV 2021] GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning This is the official implementation of our ICCV2021 paper GyroFlow. Our pres
Ladder network is a deep learning algorithm that combines supervised and unsupervised learning
This repository contains source code for the experiments in a paper titled Semi-Supervised Learning with Ladder Networks by A Rasmus, H Valpola, M Hon
Joint Unsupervised Learning (JULE) of Deep Representations and Image Clusters.
Joint Unsupervised Learning (JULE) of Deep Representations and Image Clusters. Overview This project is a Torch implementation for our CVPR 2016 paper
An implementation of Deep Graph Infomax (DGI) in PyTorch
DGI Deep Graph Infomax (Veličković et al., ICLR 2019): https://arxiv.org/abs/1809.10341 Overview Here we provide an implementation of Deep Graph Infom
Unsupervised Attributed Multiplex Network Embedding (AAAI 2020)
Unsupervised Attributed Multiplex Network Embedding (DMGI) Overview Nodes in a multiplex network are connected by multiple types of relations. However
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning
Graph-InfoClust-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu
A Python Package for Convex Regression and Frontier Estimation
pyStoNED pyStoNED is a Python package that provides functions for estimating multivariate convex regression, convex quantile regression, convex expect
Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm
An implementation of the Contrast Predictive Coding (CPC) method to train audio features in an unsupervised fashion.
CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we
Autoregressive Predictive Coding: An unsupervised autoregressive model for speech representation learning
Autoregressive Predictive Coding This repository contains the official implementation (in PyTorch) of Autoregressive Predictive Coding (APC) proposed
PyTorch implementation of MoCo: Momentum Contrast for Unsupervised Visual Representation Learning
MoCo: Momentum Contrast for Unsupervised Visual Representation Learning This is a PyTorch implementation of the MoCo paper: @Article{he2019moco, aut
Unsupervised Representation Learning by Invariance Propagation
Unsupervised Learning by Invariance Propagation This repository is the official implementation of Unsupervised Learning by Invariance Propagation. Pre
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
Learning to Classify Images without Labels This repo contains the Pytorch implementation of our paper: SCAN: Learning to Classify Images without Label
Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.
Official PyTorch implementation of the paper: "Self-Supervised Relational Reasoning for Representation Learning" (2020), Patacchiola, M., and Storkey,
Unsupervised Learning of Video Representations using LSTMs
Unsupervised Learning of Video Representations using LSTMs Code for paper Unsupervised Learning of Video Representations using LSTMs by Nitish Srivast
Code and training data for our ECCV 2016 paper on Unsupervised Learning
Shuffle and Learn (Shuffle Tuple) Created by Ishan Misra Based on the ECCV 2016 Paper - "Shuffle and Learn: Unsupervised Learning using Temporal Order
Video Representation Learning by Recognizing Temporal Transformations. In ECCV, 2020.
Video Representation Learning by Recognizing Temporal Transformations [Project Page] Simon Jenni, Givi Meishvili, and Paolo Favaro. In ECCV, 2020. Thi
Official Pytorch implementation for AAAI2021 paper (RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning)
RSPNet Official Pytorch implementation for AAAI2021 paper "RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning" [Suppleme
Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue
Realtime Unsupervised Depth Estimation from an Image This is the caffe implementation of our paper "Unsupervised CNN for single view depth estimation:
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
SfMLearner This codebase implements the system described in the paper: Unsupervised Learning of Depth and Ego-Motion from Video Tinghui Zhou, Matthew
Code for "Unsupervised State Representation Learning in Atari"
Unsupervised State Representation Learning in Atari Ankesh Anand*, Evan Racah*, Sherjil Ozair*, Yoshua Bengio, Marc-Alexandre Côté, R Devon Hjelm This
GUI for visualization and interactive editing of SMPL-family body models ie. SMPL, SMPL-X, MANO, FLAME.
Body Model Visualizer Introduction This is a simple Open3D-based GUI for SMPL-family body models. This GUI lets you play with the shape, expression, a
GUI for visualization and interactive editing of SMPL-family body models ie. SMPL, SMPL-X, MANO, FLAME.
Body Model Visualizer Introduction This is a simple Open3D-based GUI for SMPL-family body models. This GUI lets you play with the shape, expression, a
MvtecAD unsupervised Anomaly Detection
MvtecAD unsupervised Anomaly Detection This respository is the unofficial implementations of DFR: Deep Feature Reconstruction for Unsupervised Anomaly
A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation
Paper Khoi Nguyen, Sinisa Todorovic "A Weakly Supervised Amodal Segmenter with Boundary Uncertainty Estimation", accepted to ICCV 2021 Our code is mai
SIR model parameter estimation using a novel algorithm for differentiated uniformization.
TenSIR Parameter estimation on epidemic data under the SIR model using a novel algorithm for differentiated uniformization of Markov transition rate m
Affine / perspective transformation in Pose Estimation with Tensorflow 2
Pose Transformation Affine / Perspective transformation in Pose Estimation with Tensorflow 2 Introduction 이 repo는 pose estimation을 연구하고 개발하는 데 도움이 되기
Fast syllable estimation library based on pattern matching.
Syllables: A fast syllable estimator for Python Syllables is a fast, simple syllable estimator for Python. It's intended for use in places where speed
Keras implementation of PersonLab for Multi-Person Pose Estimation and Instance Segmentation.
PersonLab This is a Keras implementation of PersonLab for Multi-Person Pose Estimation and Instance Segmentation. The model predicts heatmaps and vari
MCMC samplers for Bayesian estimation in Python, including Metropolis-Hastings, NUTS, and Slice
Sampyl May 29, 2018: version 0.3 Sampyl is a package for sampling from probability distributions using MCMC methods. Similar to PyMC3 using theano to
PyTorch implementation for our AAAI 2022 Paper "Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning"
deepGCFX PyTorch implementation for our AAAI 2022 Paper "Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning" Pr
Implementation of the ALPHAMEPOL algorithm, presented in Unsupervised Reinforcement Learning in Multiple Environments.
ALPHAMEPOL This repository contains the implementation of the ALPHAMEPOL algorithm, presented in Unsupervised Reinforcement Learning in Multiple Envir
Repository for GNSS-based position estimation using a Deep Neural Network
Code repository accompanying our work on 'Improving GNSS Positioning using Neural Network-based Corrections'. In this paper, we present a Deep Neural
PyTorch implementation of Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation
Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation Introduction This is a PyTorch
TensorFlow Implementation of Unsupervised Cross-Domain Image Generation
Domain Transfer Network (DTN) TensorFlow implementation of Unsupervised Cross-Domain Image Generation. Requirements Python 2.7 TensorFlow 0.12 Pickle
Basics of 2D and 3D Human Pose Estimation.
Human Pose Estimation 101 If you want a slightly more rigorous tutorial and understand the basics of Human Pose Estimation and how the field has evolv
2D&3D human pose estimation
Human Pose Estimation Papers [CVPR 2016] - 201511 [IJCAI 2016] - 201602 Other Action Recognition with Joints-Pooled 3D Deep Convolutional Descriptors
The authors' implementation of Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations
Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations This is the authors' implementation of Unsupervised Adversarial Learning of
A simple baseline for 3d human pose estimation in PyTorch.
3d_pose_baseline_pytorch A PyTorch implementation of a simple baseline for 3d human pose estimation. You can check the original Tensorflow implementat
3D HourGlass Networks for Human Pose Estimation Through Videos
3D-HourGlass-Network 3D CNN Based Hourglass Network for Human Pose Estimation (3D Human Pose) from videos. This was my summer'18 research project. Dis
GAN-based 3D human pose estimation model for 3DV'17 paper
Tensorflow implementation for 3DV 2017 conference paper "Adversarially Parameterized Optimization for 3D Human Pose Estimation". @inproceedings{jack20
Efficient 3D human pose estimation in video using 2D keypoint trajectories
3D human pose estimation in video with temporal convolutions and semi-supervised training This is the implementation of the approach described in the
A simple baseline for 3d human pose estimation in tensorflow. Presented at ICCV 17.
3d-pose-baseline This is the code for the paper Julieta Martinez, Rayat Hossain, Javier Romero, James J. Little. A simple yet effective baseline for 3
Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
News! Aug 2020: v0.4.0 version of AlphaPose is released! Stronger tracking! Include whole body(face,hand,foot) keypoints! Colab now available. Dec 201
BERT, LDA, and TFIDF based keyword extraction in Python
BERT, LDA, and TFIDF based keyword extraction in Python kwx is a toolkit for multilingual keyword extraction based on Google's BERT and Latent Dirichl
[AAAI 2021] EMLight: Lighting Estimation via Spherical Distribution Approximation and [ICCV 2021] Sparse Needlets for Lighting Estimation with Spherical Transport Loss
EMLight: Lighting Estimation via Spherical Distribution Approximation (AAAI 2021) Update 12/2021: We release our Virtual Object Relighting (VOR) Datas
Reference code for the paper "Cross-Camera Convolutional Color Constancy" (ICCV 2021)
Cross-Camera Convolutional Color Constancy, ICCV 2021 (Oral) Mahmoud Afifi1,2, Jonathan T. Barron2, Chloe LeGendre2, Yun-Ta Tsai2, and Francois Bleibe
🏃♀️ A curated list about human motion capture, analysis and synthesis.
Awesome Human Motion 🏃♀️ A curated list about human motion capture, analysis and synthesis. Contents Introduction Human Models Datasets Data Process
This is the official PyTorch implementation of the CVPR 2020 paper "TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting".
TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting Project Page | YouTube | Paper This is the official PyTorch implementation of the C
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation
[ICCV2021] TransReID: Transformer-based Object Re-Identification [pdf] The official repository for TransReID: Transformer-based Object Re-Identificati
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition
SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec