Python Contrastive-feature-loss Resources

The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video This is the official project page of our ICCV 2

orqviz A Python package for easily visualizing the loss landscape of Variational Quantum Algorithms by Zapata Computing Inc. orqviz provides a collect

Contrastive Feature Loss for Image Prediction We provide a PyTorch implementation of our contrastive feature loss presented in: Contrastive Feature Lo

chinese_asr_demo 一个端到端的中文语音识别模型训练、测试框架 具备数据预处理、模型训练、解码、计算wer等等功能 训练数据 训练数据采用thchs_30，

Code for paper "Context-self contrastive pretraining for crop type semantic segmentation" Setting up a python environment Follow the instruction in ht

Feature Detection Based Template Matching The classification of the photos was made using the OpenCv template Matching method. Installation Use the pa

Context Encoders: Feature Learning by Inpainting CVPR 2016 [Project Website] [Imagenet Results] Sample results on held-out images: This is the trainin

A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions

FEATURE ENGINEERING Business Problem: A data preprocessing and feature engineering script for a machine learning pipeline needs to be prepared. It is

Feature-Engineering Required for a machine learning pipeline data preprocessing and variable engineering script needs to be prepared. When the dataset

CG3 This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning]. R

Image Quality Assessment using Contrastive Learning Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli and Alan C. Bovik This is the offi

A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines Understanding the results of deep neural networks is

Spectral-spatial contrastive clustering (SSCC) Yaoming Cai, Yan Liu, Zijia Zhang, Zhihua Cai, and Xiaobo Liu, Large-scale Hyperspectral Image Clusteri

FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation (ICCV 2021) This repository contains the implementation of th

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

kitty - the fast, feature-rich, cross-platform, GPU based terminal

LOFO (Leave One Feature Out) Importance calculates the importances of a set of features based on a metric of choice, for a model of choice, by iteratively removing each feature from the set, and evaluating the performance of the model, with a validation scheme of choice, based on the chosen metric.

XAI - An eXplainability toolbox for machine learning XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contai

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

DFANet This repo is an unofficial pytorch implementation of DFANet:Deep Feature Aggregation for Real-Time Semantic Segmentation log 2019.4.16 After 48

Deeplab-resnet-101 Pytorch with Lovász hinge loss Train deeplab-resnet-101 with binary Jaccard loss surrogate, the Lovász hinge, as described in http:

AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed

PyKaldi is a Python scripting layer for the Kaldi speech recognition toolkit. It provides easy-to-use, low-overhead, first-class Python wrappers for t

Aydin is a user-friendly, feature-rich, and fast image denoising tool that provides a number of self-supervised, auto-tuned, and unsupervised image denoising algorithms.

Attention-Guided-Contextual-Feature-Fusion-Network-for-Salient-Object-Detection This repo. is an implementation of ACFFNet, which is accepted for in I

discord.io A modern, easy to use, feature-rich, and async ready API wrapper for Discord written in Python. Key Features Modern Pythonic API using asyn

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

Contrastive Learning for Cold-start Recommendation This is our Pytorch implementation for the paper: Yinwei Wei, Xiang Wang, Qi Li, Liqiang Nie, Yan L

TaCL: Improve BERT Pre-training with Token-aware Contrastive Learning

Temporal Output Discrepancy for Active Learning PyTorch implementation of Semi-Supervised Active Learning with Temporal Output Discrepancy, ICCV 2021.

RTFM This repo contains the Pytorch implementation of our paper: Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Lear

Social-NCE + CrowdNav Website | Paper | Video | Social NCE + Trajectron | Social NCE + STGCNN This is an official implementation for Social NCE: Contr

Feature Importance-aware Attack(FIA) This repository contains the code for the paper: Feature Importance-aware Transferable Adversarial Attacks (ICCV

Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation This is the code relat

DetCo: Unsupervised Contrastive Learning for Object Detection arxiv link News Sparse RCNN+DetCo improves from 45.0 AP to 46.5 AP(+1.5) with 3x+ms trai

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

FREE This repository contains the reference code for the paper "FREE: Feature Refinement for Generalized Zero-Shot Learning". [arXiv][Paper] 1. Prepar

FaPN: Feature-aligned Pyramid Network for Dense Image Prediction [arXiv] [Project Page] @inproceedings{ huang2021fapn, title={{FaPN}: Feature-alig

RSC-Net: 3D Human Pose, Shape and Texture from Low-Resolution Images and Videos Implementation for "3D Human Pose, Shape and Texture from Low-Resoluti

A modern, easy to use, feature-rich, and async ready API wrapper for Discord written in Python. Key Features Modern Pythonic API using async and await

Batch processing with AWS Batch and CDK Welcome This repository demostrates provisioning the necessary infrastructure for running a job on AWS Batch u

VFedPCA+VFedAKPCA This is the official source code for the Paper: Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-

ADGCL : Adversarial Graph Augmentation to Improve Graph Contrastive Learning Introduction This repo contains the Pytorch [1] implementation of Adversa

Insect Sweeper Minesweeper clone with 3 modes of difficulty, UI scaling and custom games feature. Mines are replaced with random insects that a player

tsfeast A collection of Scikit-Learn compatible time series transformers and tools. Installation Create a virtual environment and install: From PyPi p

pingtest Description A personal project for testing internet stability, intended for use in Linux and Windows.

Instance-wise Feature Importance in Time (FIT) FIT is a framework for explaining time series perdiction models, by assigning feature importance to eve

NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.

Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering

Interpretable-contrastive-word-mover-s-embedding Paper Datasets Here is a Dropbox link to the datasets used in the paper: https://www.dropbox.com/sh/n

Improving Contrastive Learning on Imbalanced Data via Open-World Sampling Introduction Contrastive learning approaches have achieved great success in

MIRCO PyTorch implementation for paper: Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation Dependencies Python 3.

Feature Aggregation and Refinement Network for 2D Anatomical Landmark Detection Overview Localization of anatomical landmarks is essential for clinica

Structure Information is the Key: Self-Attention RoI Feature Extractor in 3D Object Detection abstract:Unlike 2D object detection where all RoI featur

Installation: pip install -e . Installing DL2: First clone DL2 in a separate directory and install it using the following commands: git clone https:/

Contrastive Self-Supervised Learning on CIFAR-10 Paper "Towards the Generalization of Contrastive Self-Supervised Learning", Weiran Huang, Mingyang Yi

Contrastive Explanations for Model Interpretability This is the repository for the paper "Contrastive Explanations for Model Interpretability", about

Token Grabber A simple Discord token grabber with base64 webhook encoding, it uses pastebin as a database to get webhook, so next time u dont get your

🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥

Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)

Intermdiate layer matters - SSL The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper. Downl

1. SaWDE.m is the main function 2. DataPartition.m is used to randomly partition the original data into training sets and test sets with a ratio of 7

Contrastive Learning with Non-Semantic Negatives This repository is the official implementation of Robust Contrastive Learning Using Negative Samples

IP-IRM [NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature". Codes will be relea

SimplEx - Explaining Latent Representations with a Corpus of Examples Code Author: Jonathan Crabbé ([email protected]) This repository contains the imp

Beehive A framework for feature exploration in Data Science Background What do we do when we finish one episode of feature exploration in a jupyter no

RCNet: Reverse Feature Pyramid and Cross-scale Shift Network for Object Detection (ACM MM'21) By Zhuofan Zong, Qianggang Cao, Biao Leng Introduction F

Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati

The official code for the NeurIPS 2021 paper Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels

We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for produce an anomaly score. Then, we merge these two score and produce merged anomaly score as a result.

NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti

Decoupled-Contrastive-Learning This repository is an implementation for the loss function proposed in Decoupled Contrastive Loss paper. Requirements P

Directed Graph Contrastive Learning The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this paper, we present the first con

Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021) Official Pytorch implementation of Unbiased Classification

Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds The why Im

Introduction PyTorch code for the ICLR 2021 paper [i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning]. @inproceedings{lee2021i

django-permissions-policy Set the draft security HTTP header Permissions-Policy (previously Feature-Policy) on your Django app. Requirements Python 3.

PyTorch implementation of MSBG hearing loss model and MBSTOI intelligibility metric This repository contains the implementation of MSBG hearing loss m

SEJE is a prototype for the paper Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering. Contents Inst

MCGC Description This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021. Datasets Results ACM DBLP IMDB Amazon photos Amazon co

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

The official code for the paper "Inverse Problems Leveraging Pre-trained Contrastive Representations" (to appear in NeurIPS 2021).

Fast Laplacian Eigenmaps in python Open-source Laplacian Eigenmaps for dimensionality reduction of large data in python. Comes with an wrapper for NMS

DIFFNet This repo is for Self-Supervised Monocular Depth Estimation with Internal Feature Fusion(arXiv), BMVC2021 A new backbone for self-supervised d

Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel

SoCo [NeurIPS 2021 Spotlight] Aligning Pretraining for Detection via Object-Level Contrastive Learning By Fangyun Wei*, Yue Gao*, Zhirong Wu, Han Hu,

Django URL Shortener Django URL Shortener is a Django app to to include URL Shortening feature in your Django Project Install this package to your Dja

Cascading Feature Extraction for Fast Point Cloud Registration This repository contains the source code for the paper [Arxive link comming soon]. Meth

PyImpetus PyImpetus is a Markov Blanket based feature selection algorithm that selects a subset of features by considering their performance both indi

feature-set-comp Compares various time-series feature sets on computational performance, within-set structure, and between-set relationships. Reposito

An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator This is a Pytorch implementation for the paper "An Empirical Study o

Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel

Spatial Location Constraint Prototype Loss for Open Set Recognition Official PyTorch implementation of "Spatial Location Constraint Prototype Loss for

Background Remover The Need It's been good long while since Microsoft first released a Teams version for Linux and yet, one of Teams' coolest features

Equalization Loss for Long-Tailed Object Recognition Jingru Tan, Changbao Wang, Buyu Li, Quanquan Li, Wanli Ouyang, Changqing Yin, Junjie Yan ⚠️ We re

Distribution-Balanced Loss [Paper] The implementation of our paper Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets (

[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.

Simple-Classifier This is a basic example of how to use several different libraries for classification and ensembling, mostly with sklearn. Example as

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa