ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1906.01905
  4. Cited By
Baby steps towards few-shot learning with multiple semantics

Baby steps towards few-shot learning with multiple semantics

5 June 2019
Eli Schwartz
Leonid Karlinsky
Rogerio Feris
Raja Giryes
A. Bronstein
    VLM
ArXivPDFHTML

Papers citing "Baby steps towards few-shot learning with multiple semantics"

13 / 13 papers shown
Title
LPN: Language-guided Prototypical Network for few-shot classification
LPN: Language-guided Prototypical Network for few-shot classification
Kaihui Cheng
Chule Yang
Xiao Liu
Naiyang Guan
Zhiyuan Wang
47
0
0
04 Jul 2023
Improving neural network representations using human similarity
  judgments
Improving neural network representations using human similarity judgments
Lukas Muttenthaler
Lorenz Linhardt
Jonas Dippel
Robert A. Vandermeulen
Katherine L. Hermann
Andrew Kyle Lampinen
Simon Kornblith
40
29
0
07 Jun 2023
Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with
  Multimodal Models
Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models
Zhiqiu Lin
Samuel Yu
Zhiyi Kuang
Deepak Pathak
Deva Ramana
VLM
15
100
0
16 Jan 2023
Multi-Modal Fusion by Meta-Initialization
Multi-Modal Fusion by Meta-Initialization
Matthew Jackson
Shreshth A. Malik
Michael T. Matthews
Yousuf Mohamed-Ahmed
26
0
0
10 Oct 2022
A Comprehensive Survey of Few-shot Learning: Evolution, Applications,
  Challenges, and Opportunities
A Comprehensive Survey of Few-shot Learning: Evolution, Applications, Challenges, and Opportunities
Yisheng Song
Ting-Yuan Wang
S. Mondal
J. P. Sahoo
SLR
50
343
0
13 May 2022
SEGA: Semantic Guided Attention on Visual Prototype for Few-Shot
  Learning
SEGA: Semantic Guided Attention on Visual Prototype for Few-Shot Learning
Fengyuan Yang
Ruiping Wang
Xilin Chen
VLM
39
35
0
08 Nov 2021
Subspace Regularizers for Few-Shot Class Incremental Learning
Subspace Regularizers for Few-Shot Class Incremental Learning
Afra Feyza Akyürek
Ekin Akyürek
Derry Wijaya
Jacob Andreas
CLL
21
59
0
13 Oct 2021
Multimodality in Meta-Learning: A Comprehensive Survey
Multimodality in Meta-Learning: A Comprehensive Survey
Yao Ma
Shilin Zhao
Weixiao Wang
Yaoman Li
Irwin King
50
53
0
28 Sep 2021
Dizygotic Conditional Variational AutoEncoder for Multi-Modal and
  Partial Modality Absent Few-Shot Learning
Dizygotic Conditional Variational AutoEncoder for Multi-Modal and Partial Modality Absent Few-Shot Learning
Yi Zhang
Sheng Huang
Xiao-song Peng
Dan Yang
22
9
0
28 Jun 2021
Counterfactual Zero-Shot and Open-Set Visual Recognition
Counterfactual Zero-Shot and Open-Set Visual Recognition
Zhongqi Yue
Tan Wang
Hanwang Zhang
Qianru Sun
Xiansheng Hua
BDL
158
192
0
01 Mar 2021
Learning from Few Samples: A Survey
Learning from Few Samples: A Survey
Nihar Bendre
Hugo Terashima-Marín
Peyman Najafirad
VLM
BDL
24
54
0
30 Jul 2020
Delta-encoder: an effective sample synthesis method for few-shot object
  recognition
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Eli Schwartz
Leonid Karlinsky
J. Shtok
Sivan Harary
Mattias Marder
Rogerio Feris
Abhishek Kumar
Raja Giryes
A. Bronstein
186
351
0
12 Jun 2018
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
329
11,681
0
09 Mar 2017
1