190 Repositories
Python few Libraries
Leaderboard, taxonomy, and curated list of few-shot object detection papers.
Leaderboard, taxonomy, and curated list of few-shot object detection papers.
[ICCV 2021 Oral] Mining Latent Classes for Few-shot Segmentation
Mining Latent Classes for Few-shot Segmentation Lihe Yang, Wei Zhuo, Lei Qi, Yinghuan Shi, Yang Gao. This codebase contains baseline of our paper Mini
Code for Recurrent Mask Refinement for Few-Shot Medical Image Segmentation (ICCV 2021).
Recurrent Mask Refinement for Few-Shot Medical Image Segmentation Steps Install any missing packages using pip or conda Preprocess each dataset using
PyTorch implementation of our ICCV paper DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection.
Introduction This repo contains the official PyTorch implementation of our ICCV paper DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection. Up
Official implementation of Few-Shot and Continual Learning with Attentive Independent Mechanisms
Few-Shot and Continual Learning with Attentive Independent Mechanisms This repository is the official implementation of Few-Shot and Continual Learnin
Animation retargeting tool for Autodesk Maya. Retargets mocap to a custom rig with a few clicks.
Animation Retargeting Tool for Maya A tool for transferring animation data between rigs or transfer raw mocap from a skeleton to a custom rig. (The sc
This is the implementation of the paper LiST: Lite Self-training Makes Efficient Few-shot Learners.
LiST (Lite Self-Training) This is the implementation of the paper LiST: Lite Self-training Makes Efficient Few-shot Learners. LiST is short for Lite S
Code to reproduce the results of the paper 'Towards Realistic Few-Shot Relation Extraction' (EMNLP 2021)
Realistic Few-Shot Relation Extraction This repository contains code to reproduce the results in the paper "Towards Realistic Few-Shot Relation Extrac
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding This repo contains the data and source code for baseline models in the NeurIPS 2
The Official Implementation of Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose [NIPS 2021].
Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Release Notes The offical PyTorch implementation of Neural View Sy
Code of the paper "Multi-Task Meta-Learning Modification with Stochastic Approximation".
Multi-Task Meta-Learning Modification with Stochastic Approximation This repository contains the code for the paper "Multi-Task Meta-Learning Modifica
Hierarchical Few-Shot Generative Models
Hierarchical Few-Shot Generative Models Giorgio Giannone, Ole Winther This repo contains code and experiments for the paper Hierarchical Few-Shot Gene
This repository is the code of the paper "Sparse Spatial Transformers for Few-Shot Learning".
🌟 Sparse Spatial Transformers for Few-Shot Learning This code implements the Sparse Spatial Transformers for Few-Shot Learning(SSFormers). Our code i
Who calls the shots? Rethinking Few-Shot Learning for Audio (WASPAA 2021)
rethink-audio-fsl This repo contains the source code for the paper "Who calls the shots? Rethinking Few-Shot Learning for Audio." (WASPAA 2021) Table
This repository is one of a few malware collections on the GitHub.
This repository is one of a few malware collections on the GitHub.
A multi-mode modulator for multi-domain few-shot classification (ICCV)
A multi-mode modulator for multi-domain few-shot classification (ICCV)
This is the code of NeurIPS'21 paper "Towards Enabling Meta-Learning from Target Models".
ST This is the code of NeurIPS 2021 paper "Towards Enabling Meta-Learning from Target Models". If you use any content of this repo for your work, plea
Fuzz a language by mixing up only few words.
afasi Fuzz a language by mixing up only few words. Status Beta. Note: The default branch is default. Use Examples Version General Help Translate Help
BMVC 2021: This is the github repository for "Few Shot Temporal Action Localization using Query Adaptive Transformers" accepted in British Machine Vision Conference (BMVC) 2021, Virtual
FS-QAT: Few Shot Temporal Action Localization using Query Adaptive Transformer Accepted as Poster in BMVC 2021 This is an official implementation in P
[WACV 2022] Contextual Gradient Scaling for Few-Shot Learning
CxGrad - Official PyTorch Implementation Contextual Gradient Scaling for Few-Shot Learning Sanghyuk Lee, Seunghyun Lee, and Byung Cheol Song In WACV 2
Code and datasets for the paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction"
KnowPrompt Code and datasets for our paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction" Requireme
Code for Findings at EMNLP 2021 paper: "Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning"
Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning This repo is for Findings at EMNLP 2021 paper: Learn Cont
A quick experiment to demonstrate Metamath formula parsing, where the grammar is embedded in a few additional 'syntax axioms'.
Warning: Hacked-up code ahead. (But it seems to work...) What it does This demonstrates an idea which I posted about several times on the Metamath mai
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
PyTorch implementation of D2C: Diffuison-Decoding Models for Few-shot Conditional Generation.
D2C: Diffuison-Decoding Models for Few-shot Conditional Generation Project | Paper PyTorch implementation of D2C: Diffuison-Decoding Models for Few-sh
Official code release for "Learned Spatial Representations for Few-shot Talking-Head Synthesis" ICCV 2021
Official code release for "Learned Spatial Representations for Few-shot Talking-Head Synthesis" ICCV 2021
Animation retargeting tool for Autodesk Maya. Retargets mocap to a custom rig with a few clicks.
Animation Retargeting Tool for Maya A tool for transferring animation data and mocap from a skeleton to a custom rig in Autodesk Maya. Installation: A
The official implementation of the CVPR 2021 paper FAPIS: a Few-shot Anchor-free Part-based Instance Segmenter
FAPIS The official implementation of the CVPR 2021 paper FAPIS: a Few-shot Anchor-free Part-based Instance Segmenter Introduction This repo is primari
The Few-Shot Bot: Prompt-Based Learning for Dialogue Systems
Few-Shot Bot: Prompt-Based Learning for Dialogue Systems This repository includes the dataset, experiments results, and code for the paper: Few-Shot B
Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation
Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation The code repository for "Audio-Visual Generalized Few-Shot Learning with
p-tuning for few-shot NLU task
p-tuning_NLU Overview 这个小项目是受乐于分享的苏剑林大佬这篇p-tuning 文章启发,也实现了个使用P-tuning进行NLU分类的任务, 思路是一样的,prompt实现方式有不同,这里是将[unused*]的embeddings参数抽取出用于初始化prompt_embed后
Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection
Novel Instances Mining with Pseudo-Margin Evaluation for Few-Shot Object Detection (NimPme) The official implementation of Novel Instances Mining with
pixelNeRF: Neural Radiance Fields from One or Few Images
pixelNeRF: Neural Radiance Fields from One or Few Images Alex Yu, Vickie Ye, Matthew Tancik, Angjoo Kanazawa UC Berkeley arXiv: http://arxiv.org/abs/2
PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation (TPAMI).
PFENet This is the implementation of our paper PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation that has been accepted to IEE
CalcuPy 📚 Create console-based calculators in a few lines of code.
CalcuPy 📚 Create console-based calculators in a few lines of code. 📌 Installation pip install calcupy 📌 Usage from calcupy import Calculator calc
Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming
Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming. Outperforming `GPT-3` on SuperGLUE Few-Shot text classification.
Convert ebooks with few clicks on Telegram!
E-Book Converter Bot A bot that converts e-books to various formats, powered by calibre! It currently supports 34 input formats and 19 output formats.
LibFewShot: A Comprehensive Library for Few-shot Learning.
LibFewShot Make few-shot learning easy. Supported Methods Meta MAML(ICML'17) ANIL(ICLR'20) R2D2(ICLR'19) Versa(NeurIPS'18) LEO(ICLR'19) MTL(CVPR'19) M
Official Implementation of Few-shot Visual Relationship Co-localization
VRC Official implementation of the Few-shot Visual Relationship Co-localization (ICCV 2021) paper project page | paper Requirements Use python = 3.8.
An original implementation of "Noisy Channel Language Model Prompting for Few-Shot Text Classification"
Channel LM Prompting (and beyond) This includes an original implementation of Sewon Min, Mike Lewis, Hannaneh Hajishirzi, Luke Zettlemoyer. "Noisy Cha
(ICCV'21) Official PyTorch implementation of Relational Embedding for Few-Shot Classification
Relational Embedding for Few-Shot Classification (ICCV 2021) Dahyun Kang, Heeseung Kwon, Juhong Min, Minsu Cho [paper], [project hompage] We propose t
Source Code For Template-Based Named Entity Recognition Using BART
Template-Based NER Source Code For Template-Based Named Entity Recognition Using BART Training Training train.py Inference inference.py Corpus ATIS (h
Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning
structshot Code and data for paper "Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning", Yi Yang and Arz
The tl;dr on a few notable transformer/language model papers + other papers (alignment, memorization, etc).
The tl;dr on a few notable transformer/language model papers + other papers (alignment, memorization, etc).
Official code for "Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer. ICCV2021".
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer. ICCV2021. Introduction We proposed a novel model training paradi
This repository contains the code for using the H3DS dataset introduced in H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction
H3DS Dataset This repository contains the code for using the H3DS dataset introduced in H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction Access
Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation
Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation This project attempted to implement the paper Putting NeRF on a
Byte-based multilingual transformer TTS for low-resource/few-shot language adaptation.
One model to speak them all 🌎 Audio Language Text ▷ Chinese 人人生而自由,在尊严和权利上一律平等。 ▷ English All human beings are born free and equal in dignity and rig
Implementation of the paper "Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning"
Self-Promoted Prototype Refinement for Few-Shot Class-Incremental Learning This is the implementation of the paper "Self-Promoted Prototype Refinement
Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"
Optimization as a Model for Few-Shot Learning This repo provides a Pytorch implementation for the Optimization as a Model for Few-Shot Learning paper.
Pytorch Implementation for CVPR2018 Paper: Learning to Compare: Relation Network for Few-Shot Learning
LearningToCompare Pytorch Implementation for Paper: Learning to Compare: Relation Network for Few-Shot Learning Howto download mini-imagenet and make
Prototypical Networks for Few shot Learning in PyTorch
Prototypical Networks for Few shot Learning in PyTorch Simple alternative Implementation of Prototypical Networks for Few Shot Learning (paper, code)
Few-shot NLP benchmark for unified, rigorous eval
FLEX FLEX is a benchmark and framework for unified, rigorous few-shot NLP evaluation. FLEX enables: First-class NLP support Support for meta-training
Few-shot Neural Architecture Search
One-shot Neural Architecture Search uses a single supernet to approximate the performance each architecture. However, this performance estimation is super inaccurate because of co-adaption among operations in supernet.
Spatial Contrastive Learning for Few-Shot Classification (SCL)
This repo contains the official implementation of Spatial Contrastive Learning for Few-Shot Classification (SCL), which presents of a novel contrastive learning method applied to few-shot image classification in order to learn more general purpose embeddings, and facilitate the test-time adaptation to novel visual categories.
Self-training for Few-shot Transfer Across Extreme Task Differences
Self-training for Few-shot Transfer Across Extreme Task Differences (STARTUP) Introduction This repo contains the official implementation of the follo
A few Windows specific scripts for PyTorch
It is a repo that contains scripts that makes using PyTorch on Windows easier. Easy Installation Update: Starting from 0.4.0, you can go to the offici
Code for 'Self-Guided and Cross-Guided Learning for Few-shot segmentation. (CVPR' 2021)'
SCL Introduction Code for 'Self-Guided and Cross-Guided Learning for Few-shot segmentation. (CVPR' 2021)' We evaluated our approach using two baseline
Implemented fully documented Particle Swarm Optimization algorithm (basic model with few advanced features) using Python programming language
Implemented fully documented Particle Swarm Optimization (PSO) algorithm in Python which includes a basic model along with few advanced features such as updating inertia weight, cognitive, social learning coefficients and maximum velocity of the particle.
Simplified diarization pipeline using some pretrained models - audio file to diarized segments in a few lines of code
simple_diarizer Simplified diarization pipeline using some pretrained models. Made to be a simple as possible to go from an input audio file to diariz
Pytorch implementation of few-shot semantic image synthesis
Few-shot Semantic Image Synthesis Using StyleGAN Prior Our method can synthesize photorealistic images from dense or sparse semantic annotations using
Adaptive Prototype Learning and Allocation for Few-Shot Segmentation (CVPR 2021)
ASGNet The code is for the paper "Adaptive Prototype Learning and Allocation for Few-Shot Segmentation" (accepted to CVPR 2021) [arxiv] Overview data/
Learning Optical Flow from a Few Matches (CVPR 2021)
Learning Optical Flow from a Few Matches This repository contains the source code for our paper: Learning Optical Flow from a Few Matches CVPR 2021 Sh
Code and data of the ACL 2021 paper: Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision
MetaAdaptRank This repository provides the implementation of meta-learning to reweight synthetic weak supervision data described in the paper Few-Shot
The implementation of PEMP in paper "Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes"
Prior-Enhanced network with Meta-Prototypes (PEMP) This is the PyTorch implementation of PEMP. Overview of PEMP Meta-Prototypes & Adaptive Prototypes
Codes for ACL-IJCNLP 2021 Paper "Zero-shot Fact Verification by Claim Generation"
Zero-shot-Fact-Verification-by-Claim-Generation This repository contains code and models for the paper: Zero-shot Fact Verification by Claim Generatio
SparseML is a libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-driven approaches built around these algorithms enable the simplification of creating faster and smaller models for the ML performance community at large.
True Few-Shot Learning with Language Models
This codebase supports using language models (LMs) for true few-shot learning: learning to perform a task using a limited number of examples from a single task distribution.
Few-NERD: Not Only a Few-shot NER Dataset
Few-NERD: Not Only a Few-shot NER Dataset This is the source code of the ACL-IJCNLP 2021 paper: Few-NERD: A Few-shot Named Entity Recognition Dataset.
Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs
Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs This is an implemetation of the paper Few-shot Relation Extraction via Baye
Few-Shot Graph Learning for Molecular Property Prediction
Few-shot Graph Learning for Molecular Property Prediction Introduction This is the source code and dataset for the following paper: Few-shot Graph Lea
[CVPR 2021] Few-shot 3D Point Cloud Semantic Segmentation
Few-shot 3D Point Cloud Semantic Segmentation Created by Na Zhao from National University of Singapore Introduction This repository contains the PyTor
PixelPick This is an official implementation of the paper "All you need are a few pixels: semantic segmentation with PixelPick."
PixelPick This is an official implementation of the paper "All you need are a few pixels: semantic segmentation with PixelPick." [Project page] [Paper
Official repository for Few-shot Image Generation via Cross-domain Correspondence (CVPR '21)
Few-shot Image Generation via Cross-domain Correspondence Utkarsh Ojha, Yijun Li, Jingwan Lu, Alexei A. Efros, Yong Jae Lee, Eli Shechtman, Richard Zh
Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch
Cross Transformers - Pytorch (wip) Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch Install $ pip install cross-t
Official PyTorch Implementation of Hypercorrelation Squeeze for Few-Shot Segmentation, arXiv 2021
Hypercorrelation Squeeze for Few-Shot Segmentation This is the implementation of the paper "Hypercorrelation Squeeze for Few-Shot Segmentation" by Juh
Official PyTorch implementation of MX-Font (Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts)
Introduction Pytorch implementation of Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Expert. | paper Song Park1
Library of various Few-Shot Learning frameworks for text classification
FewShotText This repository contains code for the paper A Neural Few-Shot Text Classification Reality Check Environment setup # Create environment pyt
git《FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding》(CVPR 2021) GitHub: [fig8]
FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding (CVPR 2021) This repo contains the implementation of our state-of-the-art fewshot ob
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Torchmeta A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch. Torchmeta contains popular meta-learning bench
All the essential resources and template code needed to understand and practice data structures and algorithms in python with few small projects to demonstrate their practical application.
Data Structures and Algorithms Python INDEX 1. Resources - Books Data Structures - Reema Thareja competitiveCoding Big-O Cheat Sheet DAA Syllabus Inte
Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification.
Easy Few-Shot Learning Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification. This repository is made for you
a feature engineering wrapper for sklearn
Few Few is a Feature Engineering Wrapper for scikit-learn. Few looks for a set of feature transformations that work best with a specified machine lear
Few-shot Learning of GPT-3
Few-shot Learning With Language Models This is a codebase to perform few-shot "in-context" learning using language models similar to the GPT-3 paper.
Face2webtoon - Despite its importance, there are few previous works applying I2I translation to webtoon.
Despite its importance, there are few previous works applying I2I translation to webtoon. I collected dataset from naver webtoon 연애혁명 and tried to transfer human faces to webtoon domain.
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
textgenrnn Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code, or quickly tr
CharacterGAN: Few-Shot Keypoint Character Animation and Reposing
CharacterGAN Implementation of the paper "CharacterGAN: Few-Shot Keypoint Character Animation and Reposing" by Tobias Hinz, Matthew Fisher, Oliver Wan
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
textgenrnn Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code, or quickly tr
Code for our method RePRI for Few-Shot Segmentation. Paper at http://arxiv.org/abs/2012.06166
Region Proportion Regularized Inference (RePRI) for Few-Shot Segmentation In this repo, we provide the code for our paper : "Few-Shot Segmentation Wit