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Uncertainty-Aware Semi-Supervised Few Shot Segmentation

Uncertainty-Aware Semi-Supervised Few Shot Segmentation

18 October 2021
Soopil Kim
Philip Chikontwe
Sang Hyun Park
ArXivPDFHTML

Papers citing "Uncertainty-Aware Semi-Supervised Few Shot Segmentation"

7 / 7 papers shown
Title
ENInst: Enhancing Weakly-supervised Low-shot Instance Segmentation
ENInst: Enhancing Weakly-supervised Low-shot Instance Segmentation
Moon Ye-Bin
D. Choi
Y. Kwon
Junsik Kim
Tae-Hyun Oh
ISeg
25
6
0
20 Feb 2023
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
CRNet: Cross-Reference Networks for Few-Shot Segmentation
CRNet: Cross-Reference Networks for Few-Shot Segmentation
Weide Liu
Chi Zhang
Guosheng Lin
Fayao Liu
SSeg
144
190
0
24 Mar 2020
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
244
1,279
0
06 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,635
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
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