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One-Shot Learning

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One-shot learning is the task of learning information about object categories from a single training example.

<span style="color:grey; opacity: 0.6">( Image credit: Siamese Neural Networks for One-shot Image Recognition )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ZVK/Talking-Heads

Few-Shot Adversarial Learning of Realistic Neural Talking Head Models

https://github.com/ZVK/talking_heads

Few-Shot Adversarial Learning of Realistic Neural Talking Head Models

https://github.com/Zelgunn/MANN_tf_keras

One-shot Learning with Memory-Augmented Neural Networks

https://github.com/Zhiwei-Z/PrompLimitTest

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/Zhiwei-Z/SeqPromp

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/Zhiwei-Z/prompzzw

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/adityagilra/archibrain

One-shot Learning with Memory-Augmented Neural Networks

https://github.com/ajfisch/few-shot-cp

Prototypical Networks for Few-shot Learning

https://github.com/akshatgarg99/FewShotLearning

Prototypical Networks for Few-shot Learning

https://github.com/alexub/jax-meta-learning

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/aliengirlliv/teachable

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/amazon-research/dse

Prototypical Networks for Few-shot Learning

https://github.com/antaradas94/MAML-waste-classification

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/asagar60/Siamese-Neural-Networks-for-One-shot-Image-Recognition

https://github.com/ash3n/Latent-Similarity

Prototypical Networks for Few-shot Learning

https://github.com/ash3n/One-shot-Memory-Augmented-NN

One-shot Learning with Memory-Augmented Neural Networks

https://github.com/ash3n/Prototypical-Network-TF

Prototypical Networks for Few-shot Learning

https://github.com/barnrang/Prototypical-network-keras-reimplementation

Prototypical Networks for Few-shot Learning

https://github.com/bhiziroglu/Siamese-Neural-Networks

https://github.com/chunbolang/DCP

One-Shot Learning for Semantic Segmentation

https://github.com/clrrrr/promp_plus

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/cnguyen10/few_shot_meta_learning

Prototypical Networks for Few-shot Learning

https://github.com/cnichkawde/MatchingNetwork

Matching Networks for One Shot Learning

https://github.com/cnielly/prototypical-networks-omniglot

Matching Networks for One Shot Learning

https://github.com/code-implementation1/Code5/tree/main/MAML

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/crashmoon/MAML-Pytorch-Multi-GPUs

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/csyanbin/MAML-Pytorch-Multi-GPUs

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/cyvius96/prototypical-network-pytorch

Prototypical Networks for Few-shot Learning

https://github.com/daiyk/daml_pytorch

One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning

https://github.com/damedollaforthree/nrml

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/debonil/hate-speech-detection

Detecting Hate Speech with GPT-3

https://github.com/dkalpakchi/ReproducingSCAPytorch

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/dragen1860/MAML-Pytorch

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/dragen1860/MAML-Pytorch-RL

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/dragen1860/Reptile-Pytorch

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/ducminhkhoi/FAPIS

One-Shot Instance Segmentation

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