165 Open source projects that are alternatives of or similar to Awesome-Few-Shot-Image-Generation

Image rotation and cropping out the black borders in TensorFlow

Artificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)

[ICCV 2021] Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation

Dialogue Knowledge Transfer Networks (DiKTNet)

Implementation of modern data augmentation techniques in TensorFlow 2.x to be used in your training pipeline.

Enhancing the BERT training with Semi-supervised Generative Adversarial Networks

A generalizable application framework for segmentation, regression, and classification using PyTorch

Library for data augmentation

Awesome Few-shot learning

Code of Empirical Bayes Transductive Meta-Learning with Synthetic Gradients

TKDE 22. CCCL: Contrastive Cascade Graph Learning.

Kaldi-based Korean ASR (한국어 음성인식) open-source project

Awesome Graph Self-Supervised Learning

An extended TSP (Time Stretched Pulse). CAPRICEP substantially replaces FVN. CAPRICEP enables interactive and real-time measurement of the linear time-invariant, the non-linear time-invariant, and random and time varying responses simultaneously.

a deep recurrent model for exchangeable data

[Medical Image Analysis] Adversarial Data Augmentation with Chained Transformations (AdvChain)

Light-weight Single Person Pose Estimator

Few-shot Keyword Spotting in Any Language and Multilingual Spoken Word Corpus

Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming. Outperforming `GPT-3` on SuperGLUE Few-Shot text classification. https://aclanthology.org/2021.acl-long.381/

PyTorch implementation of 'Squeeze and Excite' Guided Few Shot Segmentation of Volumetric Scans

Laplacian Regularized Few Shot Learning

Code for ACL'19 "Few-Shot Representation Learning for Out-Of-Vocabulary Words"

Audio degradation toolbox in python, with a command-line tool. It is useful to apply controlled degradations to audio: e.g. data augmentation, evaluation in noisy conditions, etc.

An implementation of "mixup: Beyond Empirical Risk Minimization"

Implementation of experiments in paper "Learning from Rules Generalizing Labeled Exemplars" to appear in ICLR2020 (https://openreview.net/forum?id=SkeuexBtDr)

Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning" (Neural Networks 2022 - in submission)

Data Augmentation for NLP. NLP数据增强

KitanaQA: Adversarial training and data augmentation for neural question-answering models

our code for paper 'PointCutMix: Regularization Strategy for Point Cloud Classification'

3D augmentation and transforms of 2D/3D sparse data, such as 3D triangle meshes or point clouds in Euclidean space. Extension of the Fast.ai library to train Sub-manifold Sparse Convolution Networks

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021)

A non-official 100% PyTorch implementation of META-DATASET benchmark for few-shot classification

[CVPR 2021] Few-shot 3D Point Cloud Semantic Segmentation

FSL-Mate: A collection of resources for few-shot learning (FSL).

Tensor2tensor experiment with SpecAugment

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

Learning To Compare For Text , Few shot learning in text classification

Multiclass image classification using Convolutional Neural Network

awesome few shot / meta learning papers

Code and data of ACL 2021 paper "Few-NERD: A Few-shot Named Entity Recognition Dataset"

A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.

Matching Networks for one-shot learning in tensorflow (NIPS'16)

Building an ACL tear detector to spot knee injuries from MRIs with PyTorch (MRNet)

ACL 2019 paper:Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification

中文NER的那些事儿

Implemenation of UNets for Lung Segmentation

LibFewShot: A Comprehensive Library for Few-shot Learning.

(ECCV 2020) PyTorch implementation of paper "Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild"

📄 Spatial Contrastive Learning for Few-Shot Classification (ECML/PKDD 2021).

Tensorflow implementation for paper: Learning to Compare: Relation Network for Few-Shot Learning.

finetune bert for small dataset text classification in a few-shot learning manner using ProtoNet

One-Shot Recognition of Manufacturing Defects in Steel Surfaces

Streaming over lightweight data transformations

AAAI'21: Data Augmentation for Graph Neural Networks

Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in full in this ICML 2021 paper: https://arxiv.org/abs/2102.08622.

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

[ICCV'21] Official PyTorch implementation of Relational Embedding for Few-Shot Classification

ICML'2022: Black-Box Tuning for Language-Model-as-a-Service

Tensorflow implementation of the Manifold Mixup machine learning research paper

PyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"