链接:BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification 期刊:IEEE Transactions on Image Processing 中科院分区:1区 发表时间:14 December 2020 研究动机 所提出的 Bi-Similarity Network (BSNet) 的动机。在这里,我们使用欧几里得距离和余弦距离作为特征空间中的相似性度量。欧几里得距离和...
1.整体架构 C2-Net的整体架构旨在解决Few-Shot Fine-Grained Image Classification (FS-FGIC)任务中的两个关键问题:特征提取时的噪声抑制和支持集与查询集之间的特征匹配。 2.跨层特征精炼(CLFR)模块 目标:在满足细粒度分类任务需求的同时,抑制样本级别的噪声和不可泛化的特征,减轻Few-Shot Learning设置下的过拟合...
Few-shot fine-grained image classification aims to recognize sub-categories of the same super-category given only a few labeled samples. To deal with the low inter-class variation and the high intra-class discordance, both the supervised guidance from the global view and the detail information hi...
To overcome this, we propose a fine-grained few-shot image classification algorithm based on bidirectional feature reconstruction. This algorithm introduces a Mixed Residual Attention Block (MRA Block), combining channel attention and window-based self-attention to capture local details in images. ...
State-of-the-art deep learning systems (e.g., ImageNet image classification) typically require very large training sets to achieve high accuracies. Therefore, one of the grand challenges is called few-shot learning where only a few training samples are required for good performance. In this ...
论文下载:Learning to Navigate for Fine-grained Classification Abstract 由于找出判别特征比较困难,细粒度图像分类具有挑战性。找到完全表征对象的那些微妙特征并不简单。为了处理这种情况,文章提出了一种新颖的自我监督(self-supervision )机制,可以有效地定位信息区域而无需边界框/部分注释(... ...
Moreover, as defect images are scarce, defect detection becomes a few-shot sample task falling under fine-grained visual classification (FGVC). However, in practical scenarios, discerning defects for model differentiation is complicated by the need to capture subtle features and nuances among ...
论文阅读笔记 | (TIP 2018) Object-Part Attention Model for Fine-grained Image Classification (接上一篇博文) 论文来自北京大学计算机科学技术研究所多媒体信息处理研究室(Multimedia Information Processing Lab, 简称MIPL),做细粒度图像分类。 论文下载:Object-Part Attention Model for Fine-grained Image ...
2.1 Pre-training and Fine-Tuning Baseline for few-shot image classification Guneet S Dhillon, Pratik Chaudhari, Avinash Ravichandran, and Stefano Soatto.A baseline for few-shot image classification.arXiv preprint arXiv:1909.02729, 2019. Yinbo Chen, Xiaolong Wang, Zhuang Liu, Huijuan Xu, and Trevor...
1. generic object recognition -- mini-ImageNet 2. fine-grained image classification -- CUB 3. cross-domain adaptation -- mini-ImageNet -> CUB 结果翻译过来就是--换成cosine similarity classifier的baseline就非常的有用,比你们的有些还有用。