Non-Incremental Few-Shot Detection Incremental Few-Shot Object Detection 在COCO上进行目标检测: 总结 文章链接:arxiv.org/abs/2003.0466 收录于CVPR 2020 摘要 现在的目标检测方法依赖于大量的带有充足标注的训练样本,极大地限制了只拥有少量标签的新类实现开放式调节的可扩展性。本文设定了一类逐步的少样本目标检测...
Juan-Manuel Perez-Rua, Xiatian Zhu, Timothy M. Hospedales, Tao Xiang; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 13846-13855 文章链接:Incremental Few-Shot Object Detection 代码:未开源 1.本文创新点: 现有小样本检测方法旨在解决检测模型依赖...
本文分享论文『Incremental-DETR: Incremental Few-Shot Object Detection via Self-Supervised Learning』,由新国立&哈工大提出 Incremental-DETR 进行基于自监督学习的增量 Few-Shot 目标检测,性能SOTA! 详细信息如下: 论文链接:https://arxiv.org/abs/2205.04042[1] 项目链接:未开源 01 摘要 增量few-shot目标检测的...
Incremental few-shot learning has emerged as a new and challenging area in deep learning, whose objective is to train deep learning models using very few samples of new class data, and none of the old class data. In this work we tackle the problem of batch incremental few-shot road object...
As a challenging problem in machine learning, incremental few-shot object detection (iFSD) [1] aims to incrementally detect novel classes with few examples, while keeping the previous knowledge without revisiting base classes. Here, we propose two models based on the observation that when new memo...
Incremental Few-Shot Object Detection (CVPR 2020)[23] Incremental Learning of Object Detectors without Catastrophic Forgetting (ICCV 2017)[24] 语义分割 Modeling the Background for Incremental Learning in Semantic Segmentation (CVPR 2020)[25]
简介:本文是一篇关于少量样本增量学习(Few-shot Class-Incremental Learning, FSCIL)的综述,提出了一种新的分类方法,将FSCIL分为五个子类别,并提供了广泛的文献回顾和性能评估,讨论了FSCIL的定义、挑战、相关学习问题以及在计算机视觉领域的应用。 1 介绍 ...
模型由两部分优化构成:CentreNet目标检测器,和基于类别的编码生成模型,这个生成模型不是GAN中的生成器,而是一个生成卷积核的生成器,用于生成卷积核与CentreNet中的feature-map进行卷积进行特征提取。这个编码生成器也是抄了Few-shot Object Detection via Feature Reweighting. ICCV 2019的方法,换了个名字。
论文阅读笔记《Few-shot Object Detection via Feature Reweighting》 核心思想 本文提出一种小样本目标检测算法。整体网络结构采用单阶段目标检测的形式,利用一个预测网络同时输出目标框的位置及类别结果。网络结构如下图所示 ...数据集上做微调训练,为了保证类别间的平衡性,基础数据集中每个类别的样本数量与新数据集每个...
Modern object detectors are ill-equipped to incrementally learn new emerging object classes over time due to the well-known phenomenon of catastrophic forg... Y Zhou 被引量: 0发表: 2023年 Incremental few-shot object detection via knowledge transfer As a challenging problem in machine learning, i...