# LR-FPN: Enhancing Remote Sensing Object Detection with Location Refined Feature Pyramid Network

arXiv: https://arxiv.org/abs/2404.01614 · HTML: https://mlsanity.com/paper/2404.01614/

## Key facts

- Cited by 27 papers in the map (data through 14 Oct 2026).
- Builds on 29 of its 56 references that are in the map.
- First posted on arXiv 2 Apr 2024.

## Builds on (most cited first, 29 of 29)

- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [Feature Pyramid Networks for Object Detection](https://mlsanity.com/paper/1612.03144/) (2016)
- [Squeeze-and-Excitation Networks](https://mlsanity.com/paper/1709.01507/) (2017)
- [Pyramid Scene Parsing Network](https://mlsanity.com/paper/1612.01105/) (2016)
- [CBAM: Convolutional Block Attention Module](https://mlsanity.com/paper/1807.06521/) (2018)
- [Rethinking Atrous Convolution for Semantic Image Segmentation](https://mlsanity.com/paper/1706.05587/) (2017)
- [EfficientDet: Scalable and Efficient Object Detection](https://mlsanity.com/paper/1911.09070/) (2019)
- [Path Aggregation Network for Instance Segmentation](https://mlsanity.com/paper/1803.01534/) (2018)
- [Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression](https://mlsanity.com/paper/1911.08287/) (2019)
- [NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection](https://mlsanity.com/paper/1904.07392/) (2019)
- [Coordinate Attention for Efficient Mobile Network Design](https://mlsanity.com/paper/2103.02907/) (2021)
- [R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object](https://mlsanity.com/paper/1908.05612/) (2019)
- [Arbitrary-Oriented Scene Text Detection via Rotation Proposals](https://mlsanity.com/paper/1703.01086/) (2017)
- [Lite-HRNet: A Lightweight High-Resolution Network](https://mlsanity.com/paper/2104.06403/) (2021)
- [Rotation-Sensitive Regression for Oriented Scene Text Detection](https://mlsanity.com/paper/1803.05265/) (2018)
- [AugFPN: Improving Multi-scale Feature Learning for Object Detection](https://mlsanity.com/paper/1912.05384/) (2019)
- [Automatic Ship Detection of Remote Sensing Images from Google Earth in Complex Scenes Based on Multi-Scale Rotation Dense Feature Pyramid Networks](https://mlsanity.com/paper/1806.04331/) (2018)
- [R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection](https://mlsanity.com/paper/1706.09579/) (2017)
- [GiT: Graph Interactive Transformer for Vehicle Re-identification](https://mlsanity.com/paper/2107.05475/) (2021)
- [Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identification](https://mlsanity.com/paper/2005.14684/) (2020)
- [H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection](https://mlsanity.com/paper/2210.06742/) (2022)
- [Light-Head R-CNN: In Defense of Two-Stage Object Detector](https://mlsanity.com/paper/1711.07264/) (2017)
- [IENet: Interacting Embranchment One Stage Anchor Free Detector for Orientation Aerial Object Detection](https://mlsanity.com/paper/1912.00969/) (2019)
- [Triplet Contrastive Representation Learning for Unsupervised Vehicle Re-identification](https://mlsanity.com/paper/2301.09498/) (2023)
- [Multimodal Sentiment Analysis: A Survey](https://mlsanity.com/paper/2305.07611/) (2023)
- [Contrastive Multi-view Subspace Clustering of Hyperspectral Images based on Graph Convolutional Networks](https://mlsanity.com/paper/2312.06068/) (2023)
- [Pixel-Superpixel Contrastive Learning and Pseudo-Label Correction for Hyperspectral Image Clustering](https://mlsanity.com/paper/2312.09630/) (2023)
- [Shared and Private Information Learning in Multimodal Sentiment Analysis with Deep Modal Alignment and Self-supervised Multi-Task Learning](https://mlsanity.com/paper/2305.08473/) (2023)
- [Cross-Domain Car Detection Model with Integrated Convolutional Block Attention Mechanism](https://mlsanity.com/paper/2305.20055/) (2023)

## Built on by (most cited first, 27 of 27)

- [Enhanced Self-Checkout System for Retail Based on Improved YOLOv10](https://mlsanity.com/paper/2407.21308/) (2024)
- [CCi-YOLOv8n: Enhanced Fire Detection with CARAFE and Context-Guided Modules](https://mlsanity.com/paper/2411.11011/) (2024)
- [CAF-YOLO: A Robust Framework for Multi-Scale Lesion Detection in Biomedical Imagery](https://mlsanity.com/paper/2408.01897/) (2024)
- [Efficient Feature Fusion for UAV Object Detection](https://mlsanity.com/paper/2501.17983/) (2025)
- [DASSF: Dynamic-Attention Scale-Sequence Fusion for Aerial Object Detection](https://mlsanity.com/paper/2406.12285/) (2024)
- [CMTNet: Convolutional Meets Transformer Network for Hyperspectral Images Classification](https://mlsanity.com/paper/2406.14080/) (2024)
- [Cross-modal Context Fusion and Adaptive Graph Convolutional Network for Multimodal Conversational Emotion Recognition](https://mlsanity.com/paper/2501.15063/) (2025)
- [An improved EfficientNetV2 for garbage classification](https://mlsanity.com/paper/2503.21208/) (2025)
- [YOLO-RS: Remote Sensing Enhanced Crop Detection Methods](https://mlsanity.com/paper/2504.11165/) (2025)
- [YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection](https://mlsanity.com/paper/2506.21135/) (2025)
- [Seeing the Unseen: Mask-Driven Positional Encoding and Strip-Convolution Context Modeling for Cross-View Object Geo-Localization](https://mlsanity.com/paper/2510.20247/) (2025)
- [DDNet: Deformable Convolution and Dense FPN for Surface Defect Detection in Recycled Books](https://mlsanity.com/paper/2409.04958/) (2024)
- [Dynamic Attention and Bi-directional Fusion for Safety Helmet Wearing Detection](https://mlsanity.com/paper/2411.19071/) (2024)
- [BAFPN: Bi directional alignment of features to improve localization accuracy](https://mlsanity.com/paper/2412.01859/) (2024)
- [Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection](https://mlsanity.com/paper/2412.03200/) (2024)
- [High-Precision Fabric Defect Detection via Adaptive Shape Convolutions and Large Kernel Spatial Modeling](https://mlsanity.com/paper/2501.14190/) (2025)
- [SPFFNet: Strip Perception and Feature Fusion Spatial Pyramid Pooling for Fabric Defect Detection](https://mlsanity.com/paper/2502.01445/) (2025)
- [Robust Lane Detection with Wavelet-Enhanced Context Modeling and Adaptive Sampling](https://mlsanity.com/paper/2503.18631/) (2025)
- [DGE-YOLO: Dual-Branch Gathering and Attention for Accurate UAV Object Detection](https://mlsanity.com/paper/2506.23252/) (2025)
- [DAMS:Dual-Branch Adaptive Multiscale Spatiotemporal Framework for Video Anomaly Detection](https://mlsanity.com/paper/2507.20629/) (2025)
- [EPANet: Efficient Path Aggregation Network for Underwater Fish Detection](https://mlsanity.com/paper/2508.00528/) (2025)
- [DENet: Dual-Path Edge Network with Global-Local Attention for Infrared Small Target Detection](https://mlsanity.com/paper/2509.20701/) (2025)
- [Edge-Aware and Content-Adaptive Infrared Gas Leak Detection for Industrial Safety Monitoring](https://mlsanity.com/paper/2512.23234/) (2025)
- [Interpretable Logical Anomaly Classification via Constraint Decomposition and Instruction Fine-Tuning](https://mlsanity.com/paper/2602.03530/) (2026)
- [FGAA-FPN: Foreground-Guided Angle-Aware Feature Pyramid Network for Oriented Object Detection](https://mlsanity.com/paper/2602.10710/) (2026)
- [SARES-DEIM: Sparse Mixture-of-Experts Meets DETR for Robust SAR Ship Detection](https://mlsanity.com/paper/2604.04127/) (2026)
- [A3-FPN: Asymptotic Content-Aware Pyramid Attention Network for Dense Visual Prediction](https://mlsanity.com/paper/2604.10210/) (2026)

## Abstract (arXiv)

Remote sensing target detection aims to identify and locate critical targets within remote sensing images, finding extensive applications in agriculture and urban planning. Feature pyramid networks (FPNs) are commonly used to extract multi-scale features. However, existing FPNs often overlook extracting low-level positional information and fine-grained context interaction. To address this, we propose a novel location refined feature pyramid network (LR-FPN) to enhance the extraction of shallow positional information and facilitate fine-grained context interaction. The LR-FPN consists of two primary modules: the shallow position information extraction module (SPIEM) and the contextual interaction module (CIM). Specifically, SPIEM first maximizes the retention of solid location information of the target by simultaneously extracting positional and saliency information from the low-level feature map. Subsequently, CIM injects this robust location information into different layers of the original FPN through spatial and channel interaction, explicitly enhancing the object area. Moreover, in spatial interaction, we introduce a simple local and non-local interaction strategy to learn and retain the saliency information of the object. Lastly, the LR-FPN can be readily integrated into common object detection frameworks to improve performance significantly. Extensive experiments on two large-scale remote sensing datasets (i.e., DOTAV1.0 and HRSC2016) demonstrate that the proposed LR-FPN is superior to state-of-the-art object detection approaches. Our code and models will be publicly available.