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Boosting Few-Shot Segmentation via Instance-Aware Data Augmentation and
  Local Consensus Guided Cross Attention

Boosting Few-Shot Segmentation via Instance-Aware Data Augmentation and Local Consensus Guided Cross Attention

18 January 2024
Li Guo
Haoming Liu
Yuxuan Xia
Chengyu Zhang
Xiaochen Lu
ArXivPDFHTML

Papers citing "Boosting Few-Shot Segmentation via Instance-Aware Data Augmentation and Local Consensus Guided Cross Attention"

4 / 4 papers shown
Title
TransforMatcher: Match-to-Match Attention for Semantic Correspondence
TransforMatcher: Match-to-Match Attention for Semantic Correspondence
Seungwook Kim
Juhong Min
Minsu Cho
ViT
38
32
0
23 May 2022
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight
  Transformer
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer
Zhihe Lu
Sen He
Xiatian Zhu
Li Zhang
Yi-Zhe Song
Tao Xiang
ViT
164
171
0
06 Aug 2021
Few-Shot Segmentation Without Meta-Learning: A Good Transductive
  Inference Is All You Need?
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?
Malik Boudiaf
H. Kervadec
Imtiaz Masud Ziko
Pablo Piantanida
Ismail Ben Ayed
Jose Dolz
VLM
169
186
0
11 Dec 2020
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
243
11,568
0
09 Mar 2017
1