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High-level semantic feature matters few-shot unsupervised domain
  adaptation

High-level semantic feature matters few-shot unsupervised domain adaptation

5 January 2023
Lei Yu
Wanqi Yang
Sheng Huang
Lei Wang
Ming Yang
ArXivPDFHTML

Papers citing "High-level semantic feature matters few-shot unsupervised domain adaptation"

4 / 4 papers shown
Title
Few-shot Unsupervised Domain Adaptation with Image-to-class Sparse
  Similarity Encoding
Few-shot Unsupervised Domain Adaptation with Image-to-class Sparse Similarity Encoding
Sheng Huang
Wanqi Yang
Lei Wang
Luping Zhou
Ming Yang
25
8
0
06 Aug 2021
Confidence Regularized Self-Training
Confidence Regularized Self-Training
Yang Zou
Zhiding Yu
Xiaofeng Liu
B. Kumar
Jinsong Wang
218
789
0
26 Aug 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
281
11,677
0
09 Mar 2017
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GAN
OOD
165
9,327
0
28 May 2015
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