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...
1. Cross-Layer Feature Pyramid Transformer的概念 Cross-Layer Feature Pyramid Transformer(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。它摒弃了传统的上采样操作,通过跨层特征交互实现多尺度信息的融合,从而提高了计算效率和检测性能。CFPT集成了两种精心设计的注意力模块:跨层通道注意力(CCA)和跨层...
CFPFormer: Feature-pyramid like Transformer Decoder for Segmentation and Detection Feature pyramids have been widely adopted in convolutional neural networks (CNNs) and transformers for tasks like medical image segmentation and object det... Cai, Hongyi,Rahman, Mohammad Mahdinur,Wu, Jingyu,... 被引...
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 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-...
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 ...
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 ...
FPN:Feature Pyramid Network 基于CNN固有的pyramid hierarchy,通过skip connection构建一个从上到下的通道(top-down path), 仅需要少量成本生成特征金字塔 feature pyramid,并且对于每一层的 不同尺寸的 feature pyramid都进行目标检测。 实际上就是D的改进版,D是只在最下面一层进行检测,而FPN是在每一层进行检测。
Project on the implementation of deep-learning models for ship detection on SAR images. faster-rcnnsynthetic-aperture-radarfeature-pyramid-networkcascade-rcnnship-detectionfeature-enhancementswin-transformeradjacent-feature-fusion UpdatedFeb 28, 2023 ...
Inception 模块中使用的卷积种类:k 为卷积核大小;d 为膨胀率大小 特征的可视化 不同的成本预算和成本损失的实验结果 左侧为开启的 Inception 模块数量,该可视化说明越复杂的图片模型会开启越多的 Inception 论文信息 Dynamic Feature Pyramid Networks for Object Detection...