Prompt Research
관련된 논문 참고자료 (출처: 모두의연구소)
Zero Shot Semantic Segmentation
논문 링크 - https://arxiv.org/abs/1906.00817
설명 링크 - https://deep-learning-study.tistory.com/872
Zero Shot Learning
논문 논문 링크 - https://arxiv.org/abs/2011.08641
설명 링크 - https://deep-learning-study.tistory.com/873
CaGNet - Context-aware Feature Generation for Zero-shot Semantic Segmentation
논문 링크 - https://arxiv.org/abs/2008.06893
설명 링크 - https://deep-learning-study.tistory.com/874
SIGN - Spatial-information Incorporated Generative Network for Generalized Zero-shot Semantic Segmentation
논문 링크 - https://arxiv.org/abs/2108.12517
설명 링크 - https://deep-learning-study.tistory.com/875
Metric-based approaches to meta-learning
설명 링크 - http://dmqm.korea.ac.kr/activity/seminar/301
Few-Shot Learning
https://paperswithcode.com/task/few-shot-learning
Language Models are Few-Shot Learners
설명 링크 - https://lee-soohyun.tistory.com/274
Few-shot Image Generation via Cross-domain Correspondence
논문 링크 - https://arxiv.org/abs/2104.06820
설명 링크 - https://jjuon.tistory.com/27
Meta-Learning with Task-Adaptive Loss function for Few-Shot Learning
논문 링크 - https://arxiv.org/abs/2110.03909
설명 링크 - https://jjuon.tistory.com/30
One Shot Learning, Siamese Network, Triplet Loss, Binary Loss
설명 링크 - https://wooono.tistory.com/239
Siamese Neural Networks 개념 이해하기
https://tyami.github.io/deep%20learning/Siamese-neural-networks/
Reference
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