206 Repositories
Python Label-Propagation-with-Augmented-Anchors Libraries
Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memories using approximate nearest neighbors, in Pytorch
Memorizing Transformers - Pytorch Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memori
Official repository of "BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment"
BasicVSR_PlusPlus (CVPR 2022) [Paper] [Project Page] [Code] This is the official repository for BasicVSR++. Please feel free to raise issue related to
[arXiv'22] Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation
Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation Xiao Fu1* Shangzhan Zhang1* Tianrun Chen1 Yichong Lu1 Lanyun Zhu2 Xi
A PyTorch implementation of ICLR 2022 Oral paper PiCO: Contrastive Label Disambiguation for Partial Label Learning
PiCO: Contrastive Label Disambiguation for Partial Label Learning This is a PyTorch implementation of ICLR 2022 Oral paper PiCO; also see our Project
Official Code Implementation of the paper : XAI for Transformers: Better Explanations through Conservative Propagation
Official Code Implementation of The Paper : XAI for Transformers: Better Explanations through Conservative Propagation For the SST-2 and IMDB expermin
✔👉A Centralized WebApp to Ensure Road Safety by checking on with the activities of the driver and activating label generator using NLP.
AI-For-Road-Safety Challenge hosted by Omdena Hyderabad Chapter Original Repo Link : https://github.com/OmdenaAI/omdena-india-roadsafety Final Present
The implementation our EMNLP 2021 paper "Enhanced Language Representation with Label Knowledge for Span Extraction".
LEAR The implementation our EMNLP 2021 paper "Enhanced Language Representation with Label Knowledge for Span Extraction". See below for an overview of
[arXiv'22] Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation
Panoptic NeRF Project Page | Paper | Dataset Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation Xiao Fu*, Shangzhan zhang*,
Implementation of Retrieval-Augmented Denoising Diffusion Probabilistic Models in Pytorch
Retrieval-Augmented Denoising Diffusion Probabilistic Models (wip) Implementation of Retrieval-Augmented Denoising Diffusion Probabilistic Models in P
Forward Propagation, Backward Regression and Pose Association for Hand Tracking in the Wild (CVPR 2022)
HandLer This repository contains the code and data for the following paper: Forward Propagation, Backward Regression, and Pose Association for Hand Tr
[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
Official implementation of our paper "Learning to Bootstrap for Combating Label Noise"
Learning to Bootstrap for Combating Label Noise This repo is the official implementation of our paper "Learning to Bootstrap for Combating Label Noise
Loopy belief propagation for factor graphs on discrete variables, in JAX!
PGMax implements general factor graphs for discrete probabilistic graphical models (PGMs), and hardware-accelerated differentiable loopy belief propagation (LBP) in JAX.
Pytorch implementation of Depth-conditioned Dynamic Message Propagation forMonocular 3D Object Detection
DDMP-3D Pytorch implementation of Depth-conditioned Dynamic Message Propagation forMonocular 3D Object Detection, a paper on CVPR2021. Instroduction T
PyTorch implementation of the paper: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features
Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features Estimate the noise transition matrix with f-mutual information. This co
Python command line tool and python engine to label table fields and fields in data files.
Python command line tool and python engine to label table fields and fields in data files. It could help to find meaningful data in your tables and data files or to find Personal identifable information (PII).
Mapping Conditional Distributions for Domain Adaptation Under Generalized Target Shift
This repository contains the official code of OSTAR in "Mapping Conditional Distributions for Domain Adaptation Under Generalized Target Shift" (ICLR 2022).
Multi-label classification of retinal disorders
Multi-label classification of retinal disorders This is a deep learning course project. The goal is to develop a solution, using computer vision techn
Unity Propagation in Bayesian Networks Handling Inconsistency via Unity Smoothing
This repository contains the scripts needed to generate the results from the paper Unity Propagation in Bayesian Networks Handling Inconsistency via U
A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation".
Dual-Contrastive-Learning A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation". Y
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
PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambiguation for Partial Label Learning
PiCO: Contrastive Label Disambiguation for Partial Label Learning This is a PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambig
EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients.
EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients. This repository is the official im
Predict the spans of toxic posts that were responsible for the toxic label of the posts
toxic-spans-detection An attempt at the SemEval 2021 Task 5: Toxic Spans Detection. The Toxic Spans Detection task of SemEval2021 required participant
Improving Object Detection by Label Assignment Distillation
Improving Object Detection by Label Assignment Distillation This is the official implementation of the WACV 2022 paper Improving Object Detection by L
LERP : Label-dependent and event-guided interpretable disease risk prediction using EHRs
LERP : Label-dependent and event-guided interpretable disease risk prediction using EHRs This is the code for the LERP. Dataset The dataset used is MI
"Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion"(WWW 2021)
STAR_KGC This repo contains the source code of the paper accepted by WWW'2021. "Structure-Augmented Text Representation Learning for Efficient Knowled
Learning to Segment Instances in Videos with Spatial Propagation Network
Learning to Segment Instances in Videos with Spatial Propagation Network This paper is available at the 2017 DAVIS Challenge website. Check our result
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
TResNet: High Performance GPU-Dedicated Architecture
TResNet: High Performance GPU-Dedicated Architecture paperV2 | pretrained models Official PyTorch Implementation Tal Ridnik, Hussam Lawen, Asaf Noy, I
ECLARE: Extreme Classification with Label Graph Correlations
ECLARE ECLARE: Extreme Classification with Label Graph Correlations @InProceedings{Mittal21b, author = "Mittal, A. and Sachdeva, N. and Agrawal
GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification
GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,
Automation in socks label validation
This is a project for socks card label validation where the socks card is validated comparing with the correct socks card whose coordinates are stored in the database. When the test socks card is compared with the correct socks card(master socks card) the software checks whether both test and master socks card matches or not.
MlTr: Multi-label Classification with Transformer
MlTr: Multi-label Classification with Transformer This is official implement of "MlTr: Multi-label Classification with Transformer". Abstract The task
Implementation of Memformer, a Memory-augmented Transformer, in Pytorch
Memformer - Pytorch Implementation of Memformer, a Memory-augmented Transformer, in Pytorch. It includes memory slots, which are updated with attentio
I label phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive
I label phrases on a scale of five values: negative, somewhat negative, neutral, somewhat positive, positive. Obstacles like sentence negation, sarcasm, terseness, language ambiguity, and many others make this task very challenging.
Fully Automated YouTube Channel ▶️with Added Extra Features.
Fully Automated Youtube Channel ▒█▀▀█ █▀▀█ ▀▀█▀▀ ▀▀█▀▀ █░░█ █▀▀▄ █▀▀ █▀▀█ ▒█▀▀▄ █░░█ ░░█░░ ░▒█░░ █░░█ █▀▀▄ █▀▀ █▄▄▀ ▒█▄▄█ ▀▀▀▀ ░░▀░░ ░▒█░░ ░▀▀▀ ▀▀▀░
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
Repository for the AugmentedPCA Python package.
Overview This Python package provides implementations of Augmented Principal Component Analysis (AugmentedPCA) - a family of linear factor models that
A practical ML pipeline for data labeling with experiment tracking using DVC.
Auto Label Pipeline A practical ML pipeline for data labeling with experiment tracking using DVC Goals: Demonstrate reproducible ML Use DVC to build a
Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.
Multilabel time series classification with LSTM Tensorflow implementation of model discussed in the following paper: Learning to Diagnose with LSTM Re
This repo includes the supplementary of our paper "CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels"
Supplementary Materials for CEMENT: Incomplete Multi-View Weak-Label Learning with Long-Tailed Labels This repository includes all supplementary mater
BridgeGAN - Tensorflow implementation of Bridging the Gap between Label- and Reference-based Synthesis in Multi-attribute Image-to-Image Translation.
Bridging the Gap between Label- and Reference based Synthesis(ICCV 2021) Tensorflow implementation of Bridging the Gap between Label- and Reference-ba
Official PyTorch implementation of the paper: DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample
DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample (ICCV 2021 Oral) Project | Paper Official PyTorch implementation of the pape
Pytorch implemenation of Stochastic Multi-Label Image-to-image Translation (SMIT)
SMIT: Stochastic Multi-Label Image-to-image Translation This repository provides a PyTorch implementation of SMIT. SMIT can stochastically translate a
PyTorch code for MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning
MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning PyTorch code for our ACL 2020 paper "MART: Memory-Augmented Recur
Augmented CLIP - Training simple models to predict CLIP image embeddings from text embeddings, and vice versa.
Train aug_clip against laion400m-embeddings found here: https://laion.ai/laion-400-open-dataset/ - note that this used the base ViT-B/32 CLIP model. S
Augmented Traffic Control: A tool to simulate network conditions
Augmented Traffic Control Full documentation for the project is available at http://facebook.github.io/augmented-traffic-control/. Overview Augmented
Cvdl-hw2 - Find Contour, Camera Calibration, Augmented Reality and Stereo Disparity Map
opevcvdl-hw2 This project uses openCV and Qt to achieve the requirements. Version Python 3.7 opencv-contrib-python 3.4.2.17 Matplotlib 3.1.1 pyqt5 5.1
“Robust Lightweight Facial Expression Recognition Network with Label Distribution Training”, AAAI 2021.
EfficientFace Zengqun Zhao, Qingshan Liu, Feng Zhou. "Robust Lightweight Facial Expression Recognition Network with Label Distribution Training". AAAI
Learning Saliency Propagation for Semi-supervised Instance Segmentation
Learning Saliency Propagation for Semi-supervised Instance Segmentation PyTorch Implementation This repository contains: the PyTorch implementation of
A2LP for short, ECCV2020 spotlight, Investigating SSL principles for UDA problems
Label-Propagation-with-Augmented-Anchors (A2LP) Official codes of the ECCV2020 spotlight (label propagation with augmented anchors: a simple semi-supe
Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition (NeurIPS 2019)
MLCR This is the source code for paper Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition. Xuesong Niu, Hu Han, Shiguang
This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.
This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.
Pre-training of Graph Augmented Transformers for Medication Recommendation
G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B
Self-supervised Label Augmentation via Input Transformations (ICML 2020)
Self-supervised Label Augmentation via Input Transformations Authors: Hankook Lee, Sung Ju Hwang, Jinwoo Shin (KAIST) Accepted to ICML 2020 Install de
Unsupervised Representation Learning by Invariance Propagation
Unsupervised Learning by Invariance Propagation This repository is the official implementation of Unsupervised Learning by Invariance Propagation. Pre
A script to add issues to a project in Github based on label or status.
Add Github Issues to Project (Beta) A python script to move Github issues to a next-gen (beta) Github Project Getting Started These instructions will
Simple and Robust Loss Design for Multi-Label Learning with Missing Labels
Simple and Robust Loss Design for Multi-Label Learning with Missing Labels Official PyTorch Implementation of the paper Simple and Robust Loss Design
Code to use Augmented Shapiro Wilks Stopping, as well as code for the paper "Statistically Signifigant Stopping of Neural Network Training"
This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea
POPPY (Physical Optics Propagation in Python) is a Python package that simulates physical optical propagation including diffraction
POPPY: Physical Optics Propagation in Python POPPY (Physical Optics Propagation in Python) is a Python package that simulates physical optical propaga
Code for MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks This is the code for the paper: MentorNet: Learning Data-Driven Curriculum fo
Official repository for "Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring".
RNN-MBP Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring (AAAI-2022) by Chao Zhu, Hang Dong, Jinshan Pan
QAHOI: Query-Based Anchors for Human-Object Interaction Detection (paper)
QAHOI QAHOI: Query-Based Anchors for Human-Object Interaction Detection (paper) Requirements PyTorch = 1.5.1 torchvision = 0.6.1 pip install -r requ
[NeurIPS 2021] SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning
SSUL - Official Pytorch Implementation (NeurIPS 2021) SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning Sun
Computational modelling of ray propagation through optical elements using the principles of geometric optics (Ray Tracer)
Computational modelling of ray propagation through optical elements using the principles of geometric optics (Ray Tracer) Introduction By applying the
Label data using HuggingFace's transformers and automatically get a prediction service
Label Studio for Hugging Face's Transformers Website • Docs • Twitter • Join Slack Community Transfer learning for NLP models by annotating your textu
A simple Neural Network that predicts the label for a series of handwritten digits
Neural_Network A simple Neural Network that predicts the label for a series of handwritten numbers This program tries to predict the label (1,2,3 etc.
Edge-Augmented Graph Transformer
Edge-augmented Graph Transformer Introduction This is the official implementation of the Edge-augmented Graph Transformer (EGT) as described in https:
Memory-Augmented Model Predictive Control
Memory-Augmented Model Predictive Control This repository hosts the source code for the journal article "Composing MPC with LQR and Neural Networks fo
A basic implementation of Layer-wise Relevance Propagation (LRP) in PyTorch.
Layer-wise Relevance Propagation (LRP) in PyTorch Basic unsupervised implementation of Layer-wise Relevance Propagation (Bach et al., Montavon et al.)
Extreme Dynamic Classifier Chains - XGBoost for Multi-label Classification
Extreme Dynamic Classifier Chains Classifier chains is a key technique in multi-label classification, sinceit allows to consider label dependencies ef
Code for the paper "Learning-Augmented Algorithms for Online Steiner Tree"
Learning-Augmented Algorithms for Online Steiner Tree This is the code for the paper "Learning-Augmented Algorithms for Online Steiner Tree". Requirem
Continuous Augmented Positional Embeddings (CAPE) implementation for PyTorch
PyTorch implementation of Continuous Augmented Positional Embeddings (CAPE), by Likhomanenko et al. Enhance your Transformer positional embeddings with easy-to-use augmentations!
A nutritional label for food for thought.
Lexiscore As a first effort in tackling the theme of information overload in content consumption, I've been working on the lexiscore: a nutritional la
[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Arechiga, Tengyu Ma This is the offi
This repository contains code for the paper "Disentangling Label Distribution for Long-tailed Visual Recognition", published at CVPR' 2021
Disentangling Label Distribution for Long-tailed Visual Recognition (CVPR 2021) Arxiv link Blog post This codebase is built on Causal Norm. Install co
Label Hallucination for Few-Shot Classification
Label Hallucination for Few-Shot Classification This repo covers the implementation of the following paper: Label Hallucination for Few-Shot Classific
This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition" in AAAI2022.
AimCLR This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Reco
[AAAI22] Reliable Propagation-Correction Modulation for Video Object Segmentation
Reliable Propagation-Correction Modulation for Video Object Segmentation (AAAI22) Preview version paper of this work is available at: https://arxiv.or
Official implementation of the paper Label-Efficient Semantic Segmentation with Diffusion Models
Label-Efficient Semantic Segmentation with Diffusion Models Official implementation of the paper Label-Efficient Semantic Segmentation with Diffusion
[AAAI22] Reliable Propagation-Correction Modulation for Video Object Segmentation
Reliable Propagation-Correction Modulation for Video Object Segmentation (AAAI22) Preview version paper of this work is available at: https://arxiv.or
Confidence Propagation Cluster aims to replace NMS-based methods as a better box fusion framework in 2D/3D Object detection
CP-Cluster Confidence Propagation Cluster aims to replace NMS-based methods as a better box fusion framework in 2D/3D Object detection, Instance Segme
Source code and dataset of the paper "Contrastive Adaptive Propagation Graph Neural Networks forEfficient Graph Learning"
CAPGNN Source code and dataset of the paper "Contrastive Adaptive Propagation Graph Neural Networks forEfficient Graph Learning" Paper URL: https://ar
Target Propagation via Regularized Inversion
Target Propagation via Regularized Inversion The present code implements an ideal formulation of target propagation using regularized inverses compute
Official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition" in AAAI2022.
AimCLR This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Reco
Label-Free Model Evaluation with Semi-Structured Dataset Representations
Label-Free Model Evaluation with Semi-Structured Dataset Representations Prerequisites This code uses the following libraries Python 3.7 NumPy PyTorch
The official implementation of Relative Uncertainty Learning for Facial Expression Recognition
Relative Uncertainty Learning for Facial Expression Recognition The official implementation of the following paper at NeurIPS2021: Title: Relative Unc
Label Studio is a multi-type data labeling and annotation tool with standardized output format
Website • Docs • Twitter • Join Slack Community What is Label Studio? Label Studio is an open source data labeling tool. It lets you label data types
Label-Free Model Evaluation with Semi-Structured Dataset Representations
Label-Free Model Evaluation with Semi-Structured Dataset Representations Prerequisites This code uses the following libraries Python 3.7 NumPy PyTorch
A benchmark dataset for mesh multi-label-classification based on cube engravings introduced in MeshCNN
Double Cube Engravings This script creates a dataset for multi-label mesh clasification, with an intentionally difficult setup for point cloud classif
Online Pseudo Label Generation by Hierarchical Cluster Dynamics for Adaptive Person Re-identification
Online Pseudo Label Generation by Hierarchical Cluster Dynamics for Adaptive Person Re-identification
Official repository for Hierarchical Opacity Propagation for Image Matting
HOP-Matting Official repository for Hierarchical Opacity Propagation for Image Matting 🚧 🚧 🚧 Under Construction 🚧 🚧 🚧 🚧 🚧 🚧 Coming Soon
Efficient semidefinite bounds for multi-label discrete graphical models.
Low rank solvers #################################### benchmark/ : folder with the random instances used in the paper. ############################
Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors
PSML paper: Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors PSML_IONE,PSML_ABNE,PSML_DEEPLINK,PSML_SNNA: numpy
MCML is a toolkit for semi-supervised dimensionality reduction and quantitative analysis of Multi-Class, Multi-Label data
MCML is a toolkit for semi-supervised dimensionality reduction and quantitative analysis of Multi-Class, Multi-Label data. We demonstrate its use
Scheme for training and applying a label propagation framework
Factorisation-based Image Labelling Overview This is a scheme for training and applying the factorisation-based image labelling (FIL) framework. Some
This repository will help you get label for images in Stanford Cars Dataset.
STANFORD CARS DATASET stanford-cars "The Cars dataset contains 16,185 images of 196 classes of cars. The data is split into 8,144 training images and
PyTorch implementation of Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network
hierarchical-multi-label-text-classification-pytorch Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach This
Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.
Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.