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Learning to Compare: Relation Network for Few-Shot Learning

Learning to Compare: Relation Network for Few-Shot Learning

16 November 2017
Flood Sung
Yongxin Yang
Li Zhang
Tao Xiang
Philip Torr
Timothy M. Hospedales
ArXivPDFHTML

Papers citing "Learning to Compare: Relation Network for Few-Shot Learning"

26 / 1,226 papers shown
Title
Learning to match transient sound events using attentional similarity
  for few-shot sound recognition
Learning to match transient sound events using attentional similarity for few-shot sound recognition
Szu-Yu Chou
Kai-Hsiang Cheng
J. Jang
Yi-Hsuan Yang
21
59
0
04 Dec 2018
One-Shot Instance Segmentation
One-Shot Instance Segmentation
Claudio Michaelis
Ivan Ustyuzhaninov
Matthias Bethge
Alexander S. Ecker
ISeg
37
89
0
28 Nov 2018
Generative Dual Adversarial Network for Generalized Zero-shot Learning
Generative Dual Adversarial Network for Generalized Zero-shot Learning
He Huang
Chang-Dong Wang
Philip S. Yu
Chang-Dong Wang
GAN
30
220
0
12 Nov 2018
Power Normalizing Second-order Similarity Network for Few-shot Learning
Power Normalizing Second-order Similarity Network for Few-shot Learning
Hongguang Zhang
Piotr Koniusz
18
59
0
10 Nov 2018
Few-shot learning with attention-based sequence-to-sequence models
Few-shot learning with attention-based sequence-to-sequence models
Bertrand Higy
P. Bell
19
6
0
08 Nov 2018
Zero and Few Shot Learning with Semantic Feature Synthesis and
  Competitive Learning
Zero and Few Shot Learning with Semantic Feature Synthesis and Competitive Learning
Zhiwu Lu
Jiechao Guan
Aoxue Li
Tao Xiang
An Zhao
Ji-Rong Wen
28
64
0
19 Oct 2018
Incremental Few-Shot Learning with Attention Attractor Networks
Incremental Few-Shot Learning with Attention Attractor Networks
Mengye Ren
Renjie Liao
Ethan Fetaya
R. Zemel
CLL
30
181
0
16 Oct 2018
Fast Context Adaptation via Meta-Learning
Fast Context Adaptation via Meta-Learning
L. Zintgraf
K. Shiarlis
Vitaly Kurin
Katja Hofmann
Shimon Whiteson
18
37
0
08 Oct 2018
Knowledge-guided Semantic Computing Network
Knowledge-guided Semantic Computing Network
Guangming Shi
Zhongqiang Zhang
Dahua Gao
Xuemei Xie
Yihao Feng
Xinrui Ma
Danhua Liu
18
8
0
29 Sep 2018
Towards Effective Deep Embedding for Zero-Shot Learning
Towards Effective Deep Embedding for Zero-Shot Learning
Lei Zhang
Peng Wang
Lingqiao Liu
Chunhua Shen
Wei Wei
Yanning Zhang
Anton Van Den Hengel
VLM
13
71
0
30 Aug 2018
Improving Generalization via Scalable Neighborhood Component Analysis
Improving Generalization via Scalable Neighborhood Component Analysis
Zhirong Wu
Alexei A. Efros
Stella X. Yu
BDL
22
144
0
14 Aug 2018
Deep Transfer Learning for Cross-domain Activity Recognition
Deep Transfer Learning for Cross-domain Activity Recognition
Jindong Wang
V. Zheng
Yiqiang Chen
Meiyu Huang
HAI
36
126
0
20 Jul 2018
Large Margin Few-Shot Learning
Large Margin Few-Shot Learning
Yong Wang
Xiao-Ming Wu
Qimai Li
Jiatao Gu
Wangmeng Xiang
Lei Zhang
V. Li
MQ
29
29
0
08 Jul 2018
Cross-position Activity Recognition with Stratified Transfer Learning
Cross-position Activity Recognition with Stratified Transfer Learning
Yiqiang Chen
Jindong Wang
Meiyu Huang
Han Yu
15
74
0
26 Jun 2018
Probabilistic Model-Agnostic Meta-Learning
Probabilistic Model-Agnostic Meta-Learning
Chelsea Finn
Kelvin Xu
Sergey Levine
BDL
176
666
0
07 Jun 2018
Learning to Propagate Labels: Transductive Propagation Network for
  Few-shot Learning
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Yanbin Liu
Juho Lee
Minseop Park
Saehoon Kim
Eunho Yang
Sung Ju Hwang
Yi Yang
22
666
0
25 May 2018
Meta-Learning Probabilistic Inference For Prediction
Meta-Learning Probabilistic Inference For Prediction
Jonathan Gordon
J. Bronskill
Matthias Bauer
Sebastian Nowozin
Richard Turner
BDL
45
263
0
24 May 2018
TADAM: Task dependent adaptive metric for improved few-shot learning
TADAM: Task dependent adaptive metric for improved few-shot learning
Boris N. Oreshkin
Pau Rodríguez López
Alexandre Lacoste
56
1,303
0
23 May 2018
Stacked Semantic-Guided Attention Model for Fine-Grained Zero-Shot
  Learning
Stacked Semantic-Guided Attention Model for Fine-Grained Zero-Shot Learning
YunLong Yu
Zhong Ji
Yanwei Fu
Jichang Guo
Yanwei Pang
Zhongfei Zhang
VLM
24
27
0
21 May 2018
Task-Agnostic Meta-Learning for Few-shot Learning
Task-Agnostic Meta-Learning for Few-shot Learning
Muhammad Abdullah Jamal
Guo-Jun Qi
M. Shah
52
456
0
20 May 2018
Piecewise classifier mappings: Learning fine-grained learners for novel
  categories with few examples
Piecewise classifier mappings: Learning fine-grained learners for novel categories with few examples
Xiu-Shen Wei
Peng Wang
Lingqiao Liu
Chunhua Shen
Jianxin Wu
27
124
0
11 May 2018
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes
Erin Grant
Chelsea Finn
Sergey Levine
Trevor Darrell
Thomas Griffiths
BDL
26
505
0
26 Jan 2018
Learning Non-Metric Visual Similarity for Image Retrieval
Learning Non-Metric Visual Similarity for Image Retrieval
Noa Garcia
George Vogiatzis
22
37
0
05 Sep 2017
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
422
11,715
0
09 Mar 2017
Learning a Deep Embedding Model for Zero-Shot Learning
Learning a Deep Embedding Model for Zero-Shot Learning
Li Zhang
Tao Xiang
S. Gong
SyDa
VLM
73
700
0
15 Nov 2016
Learning Deep Representations of Fine-grained Visual Descriptions
Learning Deep Representations of Fine-grained Visual Descriptions
Scott E. Reed
Zeynep Akata
Bernt Schiele
Honglak Lee
OCL
VLM
176
840
0
17 May 2016
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