Awesome-Few-shotAwesome Few-shot learning
Stars: ✭ 50 (-75.61%)
Mutual labels: meta-learning, few-shot-object-detection
mindwareAn efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.
Stars: ✭ 34 (-83.41%)
Mutual labels: meta-learning
simple-cnapsSource 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)
Stars: ✭ 88 (-57.07%)
Mutual labels: meta-learning
Nearest-Celebrity-FaceTensorflow Implementation of FaceNet: A Unified Embedding for Face Recognition and Clustering to find the celebrity whose face matches the closest to yours.
Stars: ✭ 30 (-85.37%)
Mutual labels: meta-learning
sib meta learnCode of Empirical Bayes Transductive Meta-Learning with Synthetic Gradients
Stars: ✭ 56 (-72.68%)
Mutual labels: meta-learning
DCNetDense Relation Distillation with Context-aware Aggregation for Few-Shot Object Detection, CVPR 2021
Stars: ✭ 113 (-44.88%)
Mutual labels: few-shot-object-detection
NSLImplementation for <Neural Similarity Learning> in NeurIPS'19.
Stars: ✭ 33 (-83.9%)
Mutual labels: meta-learning
meta-SRPytorch implementation of Meta-Learning for Short Utterance Speaker Recognition with Imbalance Length Pairs (Interspeech, 2020)
Stars: ✭ 58 (-71.71%)
Mutual labels: meta-learning
HebbianMetaLearningMeta-Learning through Hebbian Plasticity in Random Networks: https://arxiv.org/abs/2007.02686
Stars: ✭ 77 (-62.44%)
Mutual labels: meta-learning
StyleSpeechOfficial implementation of Meta-StyleSpeech and StyleSpeech
Stars: ✭ 161 (-21.46%)
Mutual labels: meta-learning
SAN[ECCV 2020] Scale Adaptive Network: Learning to Learn Parameterized Classification Networks for Scalable Input Images
Stars: ✭ 41 (-80%)
Mutual labels: meta-learning
FewShotDetection(ECCV 2020) PyTorch implementation of paper "Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild"
Stars: ✭ 188 (-8.29%)
Mutual labels: few-shot-object-detection
pymfePython Meta-Feature Extractor package.
Stars: ✭ 89 (-56.59%)
Mutual labels: meta-learning
FUSIONPyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"
Stars: ✭ 18 (-91.22%)
Mutual labels: meta-learning
LearningToCompare-TensorflowTensorflow implementation for paper: Learning to Compare: Relation Network for Few-Shot Learning.
Stars: ✭ 17 (-91.71%)
Mutual labels: meta-learning
MLSRSource code for ECCV2020 "Fast Adaptation to Super-Resolution Networks via Meta-Learning"
Stars: ✭ 59 (-71.22%)
Mutual labels: meta-learning
pytorch-siamese-tripletOne-Shot Learning with Triplet CNNs in Pytorch
Stars: ✭ 74 (-63.9%)
Mutual labels: meta-learning
meta-learning-progressRepository to track the progress in Meta-Learning (MtL), including the datasets and the current state-of-the-art for the most common MtL problems.
Stars: ✭ 26 (-87.32%)
Mutual labels: meta-learning
MetaHeacThis is an official implementation for "Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising"(KDD2021).
Stars: ✭ 36 (-82.44%)
Mutual labels: meta-learning
FSL-MateFSL-Mate: A collection of resources for few-shot learning (FSL).
Stars: ✭ 1,346 (+556.59%)
Mutual labels: meta-learning
