论文链接:Semi-supervised Semantic Segmentation with Prototype-based Consistency Regularization 代码链接:https://github.com/HeimingX/semi_seg_proto NeurIPS 2022的工作。斜体是我的补充。 Introduction 动机:半监督语义分割任务的一个挑战是大的类内变化,即属于同一类的区域即使在相同的图像中也可能表现出非常不同...
Non-Learnable Prototype based Nonpara-metric Semantic Segmentation 这部分作者介绍了自己的模型,构建一个不可学习参数的分割框架,该框架通过一组不可学习的类原型进行密集预测,并通过原型锚定度量学习直接监督像素嵌入空间 训练阶段作者的模型 Non-Learnable Prototype based Pixel Classification 在作者的模型中,loss可以...
Using a single prototype acquired directly from the support image to segment the query image causes semantic ambiguity. In this paper, we propose prototype mixture models (PMMs), which correlate diverse image regions with multiple prototypes to enforce the prototype-based semantic representation. ...
[小样本图像分割]Few-Shot Semantic Segmentation with Prototype Learning,程序员大本营,技术文章内容聚合第一站。
Code Issues Pull requests CVPR2022 (Oral) - Rethinking Semantic Segmentation: A Prototype View prototype deep-learning clustering transformer segmentation metric-learning fcn semantic-segmentation nonparametric softmax nearest-neighbours-classifier Updated Jun 30, 2022 Python pret...
A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learning by Binhui Xie, Mingjia Li, Shuang Li. Update 2021/11/25: arXiv version of SPCL is available. 2022/06/24: Code is released. If you find it useful for your research, please cite @artic...
论文阅读笔记《PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment》,程序员大本营,技术文章内容聚合第一站。
简介:本文介绍了ICCV 2019的一篇关于小样本图像语义分割的论文《PANet: Few-Shot Image Semantic Segmentation With Prototype Alignment》。PANet通过度量学习方法,从支持集中的少量标注样本中学习类的原型表示,并通过非参数度量学习对查询图像进行分割。该方法在PASCAL-5i数据集上取得了显著的性能提升,1-shot和5-shot设置...
prototype-based methods may overlook some local and crucial semantic features of the target class in support images, potentially resulting in rough segmentation of the target class in the query image, particularly for objects with complex appearances. Secondly, while pixel-level methods have significantl...
In this paper, we propose a novel few-shot semantic segmentation framework based on the prototype representation. Our key idea is to decompose the holistic class representation into a set of part-aware prototypes, capable of capturing diverse and fine-grained object features. In addition, we ...