在transformer中最重要的是attention机制的灵活运用,在NLN中将图像经过特征提取网络将图像大小降低到14x14或7x7,再通过如下Non Local Block结构进行非局部信息的提取,使得模型会将注意力放在有利于识别任务的像素位置上,具体如上图所示。 Feature Pyramid Transformer 在non-local 交互操作中,其使用feature map作为values (...
1. Cross-Layer Feature Pyramid Transformer(CFPT)的基本原理 CFPT 是一种专为航拍图像中小目标检测设计的特征金字塔网络。它避免了传统的上采样操作,而是通过跨层交互直接实现特征融合,减少了信息丢失和计算复杂度。CFPT 的核心在于两种精心设计的注意力模块: 跨层通道注意力(CCA):通过沿通道维度划分标记组来实现跨...
To this end, we propose a fully active feature interaction across both space and scales, called Feature Pyramid Transformer (FPT). It transforms any feature pyramid into another feature pyramid of the same size but with richer contexts, by using three specially designed transformers in self-level...
简介:本文介绍了一个在空间和尺度上全活跃特征交互(fully active feature interaction across both space and scales)的特征金字塔transformer模型,简称FPT。该模型将transformer和Feature Pyramid结合,可用于像素级的任务,在论文中作者进行了目标检测和实力分割,都取得了比较好的效果。为了讲解清楚,若有transformer不懂的读者...
To this end, we propose a fully active feature interaction across both space and scales, called Feature Pyramid Transformer (FPT). It transforms any feature pyramid into another feature pyramid of the same size but with richer contexts, by using three specially designed transformers in self-level...
In thispaper, we propose the cross-layer feature pyramid transformer designed for small object detection in aerial images. Below is the performance comparison with other feature pyramid networks based on RetinaNet on the VisDrone-2019 DET dataset. ...
可以看到这篇文章所有实验都只和 FPN 对比,可能是因为确实大幅不如 Transformer,感兴趣的朋友可以翻到前几篇关于 Transformer 的文章对比下同数据集实验结果。 论文信息 FaPN: Feature-aligned Pyramid Network for Dense Image Prediction https://arxiv.org/pdf/2108.07058.pdf ...
虽然没比过 Vision Transformer 结构,但作者称毕竟这篇文章是专注于核心的,就第一张图中间的部分。如果进一步将 Transformer 结构考虑进输出端,作者相信结果一定会更好～ 论文信息 Trident Pyramid Networks: the Importance of Processing at the Feature Pyramid Level for Better Object Detection arxiv.org/pdf/2110...
To resolve this, we propose Retro-FPN to model the per-point feature prediction as an explicit and retrospective refining process, which goes through all the pyramid layers to extract semantic features explicitly for each point. Its key novelty is a retro-transformer for summarizing semantic ...
computer-visiontensorflowdetectiontransformerfaster-rcnncocoobject-detectioninstance-segmentationfeature-pyramid-networktensorflow2detectionsdetr UpdatedNov 21, 2022 Python yuhuan-wu/RDPNet Star44 Code Issues Pull requests (IEEE TIP 2021) Regularized Densely-connected Pyramid Network for Salient Instance Segmentati...