RankDNN: Learning to Rank for Few-shot Learning

28 November 2022

Papers citing "RankDNN: Learning to Rank for Few-shot Learning"

8 / 8 papers shown

Title
Task Affinity with Maximum Bipartite Matching in Few-Shot Learning Cat P. Le Juncheng Dong Mohammadreza Soltani Vahid Tarokh 26 11 0 05 Oct 2021
Free Lunch for Few-shot Learning: Distribution Calibration Shuo Yang Lu Liu Min Xu OODD 210 322 0 16 Jan 2021
XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning Sung Whan Yoon Do-Yeon Kim Jun Seo Jaekyun Moon CLL 173 46 0 19 Mar 2020
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning Yinbo Chen Zhuang Liu Huijuan Xu Trevor Darrell Xiaolong Wang 166 340 0 09 Mar 2020
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 Chelsea Finn Pieter Abbeel Sergey Levine OOD 314 11,681 0 09 Mar 2017
Borrowing Treasures from the Wealthy: Deep Transfer Learning through Selective Joint Fine-tuning Weifeng Ge Yizhou Yu 88 233 0 28 Feb 2017
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,194 0 01 Sep 2014