ReMP: Rectified Metric Propagation for Few-Shot Learning

12/02/2020
by   fcq, et al.
0

Few-shot learning features the capability of generalizing from a few examples. In this paper, we first identify that a discriminative feature space, namely a rectified metric space, that is learned to maintain the metric consistency from training to testing, is an essential component to the success of metric-based few-shot learning. Numerous analyses indicate that a simple modification of the objective can yield substantial performance gains. The resulting approach, called rectified metric propagation (ReMP), further optimizes an attentive prototype propagation network, and applies a repulsive force to make confident predictions. Extensive experiments demonstrate that the proposed ReMP is effective and efficient, and outperforms the state of the arts on various standard few-shot learning datasets.

READ FULL TEXT

page 7

page 8

research
05/23/2018

TADAM: Task dependent adaptive metric for improved few-shot learning

Few-shot learning has become essential for producing models that general...
research
05/28/2021

One-shot Learning with Absolute Generalization

One-shot learning is proposed to make a pretrained classifier workable o...
research
06/05/2019

Discriminative Few-Shot Learning Based on Directional Statistics

Metric-based few-shot learning methods try to overcome the difficulty du...
research
05/25/2018

Transductive Propagation Network for Few-shot Learning

Few-shot learning aims to build a learner that quickly generalizes to no...
research
11/16/2022

On Measuring the Intrinsic Few-Shot Hardness of Datasets

While advances in pre-training have led to dramatic improvements in few-...
research
05/09/2020

Memory-Augmented Relation Network for Few-Shot Learning

Metric-based few-shot learning methods concentrate on learning transfera...
research
11/19/2020

Hybrid Consistency Training with Prototype Adaptation for Few-Shot Learning

Few-Shot Learning (FSL) aims to improve a model's generalization capabil...

Please sign up or login with your details

Forgot password? Click here to reset