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A Baseline for Few-Shot Image Classification

A Baseline for Few-Shot Image Classification

6 September 2019
Guneet Singh Dhillon
Pratik Chaudhari
Avinash Ravichandran
Stefano Soatto
ArXivPDFHTML

Papers citing "A Baseline for Few-Shot Image Classification"

43 / 43 papers shown
Title
Few-Shot Learning from Gigapixel Images via Hierarchical Vision-Language Alignment and Modeling
Few-Shot Learning from Gigapixel Images via Hierarchical Vision-Language Alignment and Modeling
Bryan Wong
Jong Woo Kim
Huazhu Fu
Mun Yi
VLM
161
0
0
23 May 2025
Chain-of-Thought Textual Reasoning for Few-shot Temporal Action Localization
Chain-of-Thought Textual Reasoning for Few-shot Temporal Action Localization
Hongwei Ji
Wulian Yun
Mengshi Qi
Huadong Ma
LRM
364
0
0
18 Apr 2025
Transductive One-Shot Learning Meet Subspace Decomposition
Transductive One-Shot Learning Meet Subspace Decomposition
Kyle Stein
A. Mahyari
Guillermo Francia III
Eman El-Sheikh
VLM
92
1
0
01 Apr 2025
Prospective Learning: Learning for a Dynamic Future
Prospective Learning: Learning for a Dynamic Future
Ashwin De Silva
Rahul Ramesh
Rubing Yang
Siyu Yu
Joshua T. Vogelstein
Pratik Chaudhari
AI4TS
137
0
0
31 Oct 2024
Flatness Improves Backbone Generalisation in Few-shot Classification
Flatness Improves Backbone Generalisation in Few-shot Classification
Rui Li
Martin Trapp
Talal Alrawajfeh
Arno Solin
93
0
0
11 Apr 2024
PARMESAN: Parameter-Free Memory Search and Transduction for Dense Prediction Tasks
PARMESAN: Parameter-Free Memory Search and Transduction for Dense Prediction Tasks
Philip Matthias Winter
M. Wimmer
David Major
Dimitrios Lenis
Astrid Berg
Theresa Neubauer
Gaia Romana De Paolis
Johannes Novotny
Sophia Ulonska
Katja Bühler
110
0
0
18 Mar 2024
Embracing the Disharmony in Medical Imaging: A Simple and Effective
  Framework for Domain Adaptation
Embracing the Disharmony in Medical Imaging: A Simple and Effective Framework for Domain Adaptation
Rongguang Wang
Pratik Chaudhari
Christos Davatzikos
OOD
93
52
0
23 Mar 2021
Learning Internal Representations (COLT 1995)
Learning Internal Representations (COLT 1995)
Jonathan Baxter
SSL
AI4CE
103
400
0
13 Nov 2019
Few-Shot Learning with Embedded Class Models and Shot-Free Meta Training
Few-Shot Learning with Embedded Class Models and Shot-Free Meta Training
Avinash Ravichandran
Rahul Bhotika
Stefano Soatto
65
170
0
10 May 2019
A Closer Look at Few-shot Classification
A Closer Look at Few-shot Classification
Wei-Yu Chen
Yen-Cheng Liu
Z. Kira
Y. Wang
Jia-Bin Huang
104
1,761
0
08 Apr 2019
Meta-Learning with Differentiable Convex Optimization
Meta-Learning with Differentiable Convex Optimization
Kwonjoon Lee
Subhransu Maji
Avinash Ravichandran
Stefano Soatto
91
1,267
0
07 Apr 2019
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few
  Examples
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Eleni Triantafillou
Tyler Lixuan Zhu
Vincent Dumoulin
Pascal Lamblin
Utku Evci
...
Ross Goroshin
Carles Gelada
Kevin Swersky
Pierre-Antoine Manzagol
Hugo Larochelle
145
616
0
07 Mar 2019
Analyzing and Improving Representations with the Soft Nearest Neighbor
  Loss
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
Nicholas Frosst
Nicolas Papernot
Geoffrey E. Hinton
44
161
0
05 Feb 2019
Bag of Tricks for Image Classification with Convolutional Neural
  Networks
Bag of Tricks for Image Classification with Convolutional Neural Networks
Tong He
Zhi-Li Zhang
Hang Zhang
Zhongyue Zhang
Junyuan Xie
Mu Li
278
1,413
0
04 Dec 2018
Highly Scalable Deep Learning Training System with Mixed-Precision:
  Training ImageNet in Four Minutes
Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes
Xianyan Jia
Shutao Song
W. He
Yangzihao Wang
Haidong Rong
...
Li Yu
Tiegang Chen
Guangxiao Hu
Shaoshuai Shi
Xiaowen Chu
64
383
0
30 Jul 2018
Meta-Learning with Latent Embedding Optimization
Meta-Learning with Latent Embedding Optimization
Andrei A. Rusu
Dushyant Rao
Jakub Sygnowski
Oriol Vinyals
Razvan Pascanu
Simon Osindero
R. Hadsell
132
1,370
0
16 Jul 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
86
667
0
25 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
93
1,312
0
23 May 2018
Meta-learning with differentiable closed-form solvers
Meta-learning with differentiable closed-form solvers
Luca Bertinetto
João F. Henriques
Philip Torr
Andrea Vedaldi
ODL
80
928
0
21 May 2018
Dynamic Few-Shot Visual Learning without Forgetting
Dynamic Few-Shot Visual Learning without Forgetting
Spyros Gidaris
N. Komodakis
VLM
59
1,129
0
25 Apr 2018
On First-Order Meta-Learning Algorithms
On First-Order Meta-Learning Algorithms
Alex Nichol
Joshua Achiam
John Schulman
221
2,229
0
08 Mar 2018
Meta-Learning for Semi-Supervised Few-Shot Classification
Meta-Learning for Semi-Supervised Few-Shot Classification
Mengye Ren
Eleni Triantafillou
S. S. Ravi
Jake C. Snell
Kevin Swersky
J. Tenenbaum
Hugo Larochelle
R. Zemel
SSL
65
1,282
0
02 Mar 2018
Few-Shot Learning with Graph Neural Networks
Few-Shot Learning with Graph Neural Networks
Victor Garcia Satorras
Joan Bruna
GNN
167
1,239
0
10 Nov 2017
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
269
9,743
0
25 Oct 2017
Mixed Precision Training
Mixed Precision Training
Paulius Micikevicius
Sharan Narang
Jonah Alben
G. Diamos
Erich Elsen
...
Boris Ginsburg
Michael Houston
Oleksii Kuchaiev
Ganesh Venkatesh
Hao Wu
149
1,792
0
10 Oct 2017
Few-Shot Image Recognition by Predicting Parameters from Activations
Few-Shot Image Recognition by Predicting Parameters from Activations
Siyuan Qiao
Chenxi Liu
Wei Shen
Alan Yuille
VLM
65
555
0
12 Jun 2017
Good Semi-supervised Learning that Requires a Bad GAN
Good Semi-supervised Learning that Requires a Bad GAN
Zihang Dai
Zhilin Yang
Fan Yang
William W. Cohen
Ruslan Salakhutdinov
GAN
45
483
0
27 May 2017
No Fuss Distance Metric Learning using Proxies
No Fuss Distance Metric Learning using Proxies
Yair Movshovitz-Attias
Alexander Toshev
Thomas Leung
Sergey Ioffe
Saurabh Singh
80
640
0
21 Mar 2017
Prototypical Networks for Few-shot Learning
Prototypical Networks for Few-shot Learning
Jake C. Snell
Kevin Swersky
R. Zemel
271
8,114
0
15 Mar 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
806
11,866
0
09 Mar 2017
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
577
28,999
0
09 Sep 2016
SGDR: Stochastic Gradient Descent with Warm Restarts
SGDR: Stochastic Gradient Descent with Warm Restarts
I. Loshchilov
Frank Hutter
ODL
288
8,091
0
13 Aug 2016
Regularization With Stochastic Transformations and Perturbations for
  Deep Semi-Supervised Learning
Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning
Mehdi S. M. Sajjadi
Mehran Javanmardi
Tolga Tasdizen
BDL
77
1,111
0
14 Jun 2016
Matching Networks for One Shot Learning
Matching Networks for One Shot Learning
Oriol Vinyals
Charles Blundell
Timothy Lillicrap
Koray Kavukcuoglu
Daan Wierstra
VLM
337
7,316
0
13 Jun 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
312
7,971
0
23 May 2016
Identity Mappings in Deep Residual Networks
Identity Mappings in Deep Residual Networks
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
330
10,172
0
16 Mar 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.9K
193,426
0
10 Dec 2015
Rethinking the Inception Architecture for Computer Vision
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
Vincent Vanhoucke
Sergey Ioffe
Jonathon Shlens
Z. Wojna
3DV
BDL
717
27,303
0
02 Dec 2015
Distributional Smoothing with Virtual Adversarial Training
Distributional Smoothing with Virtual Adversarial Training
Takeru Miyato
S. Maeda
Masanori Koyama
Ken Nakae
S. Ishii
89
458
0
02 Jul 2015
Cyclical Learning Rates for Training Neural Networks
Cyclical Learning Rates for Training Neural Networks
L. Smith
ODL
171
2,517
0
03 Jun 2015
Gradient-based Hyperparameter Optimization through Reversible Learning
Gradient-based Hyperparameter Optimization through Reversible Learning
D. Maclaurin
David Duvenaud
Ryan P. Adams
DD
207
944
0
11 Feb 2015
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
419
43,234
0
11 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.4K
149,842
0
22 Dec 2014
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