Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation

06/01/2021
by   Binghao Liu, et al.
0

Encouraging progress in few-shot semantic segmentation has been made by leveraging features learned upon base classes with sufficient training data to represent novel classes with few-shot examples. However, this feature sharing mechanism inevitably causes semantic aliasing between novel classes when they have similar compositions of semantic concepts. In this paper, we reformulate few-shot segmentation as a semantic reconstruction problem, and convert base class features into a series of basis vectors which span a class-level semantic space for novel class reconstruction. By introducing contrastive loss, we maximize the orthogonality of basis vectors while minimizing semantic aliasing between classes. Within the reconstructed representation space, we further suppress interference from other classes by projecting query features to the support vector for precise semantic activation. Our proposed approach, referred to as anti-aliasing semantic reconstruction (ASR), provides a systematic yet interpretable solution for few-shot learning problems. Extensive experiments on PASCAL VOC and MS COCO datasets show that ASR achieves strong results compared with the prior works.

READ FULL TEXT

page 1

page 8

research
03/24/2023

Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation

Current methods for few-shot segmentation (FSSeg) have mainly focused on...
research
10/11/2020

Generalized Few-Shot Semantic Segmentation

Training semantic segmentation models requires a large amount of finely ...
research
08/06/2021

Learning Meta-class Memory for Few-Shot Semantic Segmentation

Currently, the state-of-the-art methods treat few-shot semantic segmenta...
research
05/12/2023

Quaternion-valued Correlation Learning for Few-Shot Semantic Segmentation

Few-shot segmentation (FSS) aims to segment unseen classes given only a ...
research
11/16/2022

Interclass Prototype Relation for Few-Shot Segmentation

Traditional semantic segmentation requires a large labeled image dataset...
research
10/15/2022

Prediction Calibration for Generalized Few-shot Semantic Segmentation

Generalized Few-shot Semantic Segmentation (GFSS) aims to segment each i...
research
10/22/2021

Few-shot Semantic Segmentation with Self-supervision from Pseudo-classes

Despite the success of deep learning methods for semantic segmentation, ...

Please sign up or login with your details

Forgot password? Click here to reset