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Concept-wise Fine-tuning Matters in Preventing Negative Transfer

Concept-wise Fine-tuning Matters in Preventing Negative Transfer

12 November 2023
Yunqiao Yang
Long-Kai Huang
Ying Wei
ArXivPDFHTML

Papers citing "Concept-wise Fine-tuning Matters in Preventing Negative Transfer"

5 / 5 papers shown
Title
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
296
7,434
0
11 Nov 2021
Rectifying the Shortcut Learning of Background for Few-Shot Learning
Rectifying the Shortcut Learning of Background for Few-Shot Learning
Xu Luo
Longhui Wei
Liangjiang Wen
Jinrong Yang
Lingxi Xie
Zenglin Xu
Qi Tian
34
86
0
16 Jul 2021
Unleashing the Power of Contrastive Self-Supervised Visual Models via
  Contrast-Regularized Fine-Tuning
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning
Yifan Zhang
Bryan Hooi
Dapeng Hu
Jian Liang
Jiashi Feng
71
64
0
12 Feb 2021
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
243
3,367
0
09 Mar 2020
Semantic Understanding of Scenes through the ADE20K Dataset
Semantic Understanding of Scenes through the ADE20K Dataset
Bolei Zhou
Hang Zhao
Xavier Puig
Tete Xiao
Sanja Fidler
Adela Barriuso
Antonio Torralba
SSeg
253
1,824
0
18 Aug 2016
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