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 (...
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...
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...
RTDETR改进-最新的FPN变种High-level Screening-feature Pyramid Networks,并对其进行二次创新 8399 -- 3:19 App YOLOV8损失函数改进大合集,支持几十种各类型损失函数的替换~ 4757 -- 7:19 App YOLOV8改进-特征聚焦扩散金字塔网络Focusing Diffusion Pyramid Network 8359 2 11:24 App YOLOv8改进涨点:项目文件...
Cross-Layer Feature Pyramid Transformer for Small Object Detection in Aerial Images This repository provides the official PyTorch implementation of CFPT. In this paper, we propose the cross-layer feature pyramid transformer designed for small object detection in aerial images. Below is the performance ...
In this paper, we introduce the Cross-Layer Feature Pyramid Transformer (CFPT), a novel upsampler-free feature pyramid network designed specifically for small object detection in aerial images. CFPT incorporates two meticulously designed attention blocks with linear computational complexity: the Cross-...
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...
* 其他: An efficient and effective technique that supports MAE-style MIM Pre-training for popular Pyramid-based Vision Transformers (e.g., PVT, Swin) * 摘要: 蒙面自动编码器(MAE)最近通过优雅的不对称编码器设计设计了视觉自我划分区域的趋势,该设计可显着优化预训练效率和微调准确性。值得注意的是,不...