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A Closer Look at Few-shot Classification Again

A Closer Look at Few-shot Classification Again

28 January 2023
Xu Luo
Hao Wu
Ji Zhang
Lianli Gao
Jing Xu
Jingkuan Song
ArXivPDFHTML

Papers citing "A Closer Look at Few-shot Classification Again"

19 / 19 papers shown
Title
Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
Qi Xu
J. Zhu
D. Zhou
Hao Chen
Y. Liu
Jiangrong Shen
Qiang Zhang
18
0
0
12 May 2025
UNEM: UNrolled Generalized EM for Transductive Few-Shot Learning
UNEM: UNrolled Generalized EM for Transductive Few-Shot Learning
Long Zhou
Fereshteh Shakeri
Aymen Sadraoui
Mounir Kaaniche
J. Pesquet
Ismail Ben Ayed
VLM
79
0
0
21 Dec 2024
Transforming Game Play: A Comparative Study of DCQN and DTQN
  Architectures in Reinforcement Learning
Transforming Game Play: A Comparative Study of DCQN and DTQN Architectures in Reinforcement Learning
William A. Stigall
43
0
0
14 Oct 2024
Flatness Improves Backbone Generalisation in Few-shot Classification
Flatness Improves Backbone Generalisation in Few-shot Classification
Rui Li
Martin Trapp
Marcus Klasson
Arno Solin
36
0
0
11 Apr 2024
Few and Fewer: Learning Better from Few Examples Using Fewer Base
  Classes
Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes
Raphael Lafargue
Yassir Bendou
Bastien Pasdeloup
J. Diguet
Ian Reid
Vincent Gripon
Jack Valmadre
12
0
0
29 Jan 2024
TransMed: Large Language Models Enhance Vision Transformer for
  Biomedical Image Classification
TransMed: Large Language Models Enhance Vision Transformer for Biomedical Image Classification
Kaipeng Zheng
Weiran Huang
Lichao Sun
LM&MA
MedIm
VLM
19
0
0
12 Dec 2023
Alleviating the Sample Selection Bias in Few-shot Learning by Removing
  Projection to the Centroid
Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid
Jing Xu
Xu Luo
Xinglin Pan
Wenjie Pei
Yanan Li
Zenglin Xu
36
21
0
30 Oct 2022
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
258
7,337
0
11 Nov 2021
Open-Set Recognition: a Good Closed-Set Classifier is All You Need?
Open-Set Recognition: a Good Closed-Set Classifier is All You Need?
S. Vaze
Kai Han
Andrea Vedaldi
Andrew Zisserman
BDL
158
401
0
12 Oct 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
32
86
0
16 Jul 2021
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
283
5,723
0
29 Apr 2021
CrossTransformers: spatially-aware few-shot transfer
CrossTransformers: spatially-aware few-shot transfer
Carl Doersch
Ankush Gupta
Andrew Zisserman
ViT
201
328
0
22 Jul 2020
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning
Yinbo Chen
Zhuang Liu
Huijuan Xu
Trevor Darrell
Xiaolong Wang
158
339
0
09 Mar 2020
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
238
3,359
0
09 Mar 2020
TaskNorm: Rethinking Batch Normalization for Meta-Learning
TaskNorm: Rethinking Batch Normalization for Meta-Learning
J. Bronskill
Jonathan Gordon
James Requeima
Sebastian Nowozin
Richard E. Turner
54
89
0
06 Mar 2020
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
226
4,424
0
23 Jan 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
948
20,214
0
17 Apr 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
243
11,568
0
09 Mar 2017
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
L. V. D. van der Maaten
Kilian Q. Weinberger
PINN
3DV
244
35,884
0
25 Aug 2016
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