# IENet: Interacting Embranchment One Stage Anchor Free Detector for Orientation Aerial Object Detection

arXiv: https://arxiv.org/abs/1912.00969 · HTML: https://mlsanity.com/paper/1912.00969/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Dec 2019.

## Built on by (most cited first, 17 of 17)

- [Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss](https://mlsanity.com/paper/2101.11952/) (2021)
- [The KFIoU Loss for Rotated Object Detection](https://mlsanity.com/paper/2201.12558/) (2022)
- [AO2-DETR: Arbitrary-Oriented Object Detection Transformer](https://mlsanity.com/paper/2205.12785/) (2022)
- [LR-FPN: Enhancing Remote Sensing Object Detection with Location Refined Feature Pyramid Network](https://mlsanity.com/paper/2404.01614/) (2024)
- [A General Gaussian Heatmap Label Assignment for Arbitrary-Oriented Object Detection](https://mlsanity.com/paper/2109.12848/) (2021)
- [RSDet++: Point-based Modulated Loss for More Accurate Rotated Object Detection](https://mlsanity.com/paper/2109.11906/) (2021)
- [FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection](https://mlsanity.com/paper/2111.10780/) (2021)
- [Oriented object detection in optical remote sensing images using deep learning: a survey](https://mlsanity.com/paper/2302.10473/) (2023)
- [Learning Calibrated-Guidance for Object Detection in Aerial Images](https://mlsanity.com/paper/2103.11399/) (2021)
- [DAFNe: A One-Stage Anchor-Free Approach for Oriented Object Detection](https://mlsanity.com/paper/2109.06148/) (2021)
- [EARL: An Elliptical Distribution aided Adaptive Rotation Label Assignment for Oriented Object Detection in Remote Sensing Images](https://mlsanity.com/paper/2301.05856/) (2023)
- [LO-Det: Lightweight Oriented Object Detection in Remote Sensing Images](https://mlsanity.com/paper/2209.07709/) (2022)
- [OSKDet: Towards Orientation-sensitive Keypoint Localization for Rotated Object Detection](https://mlsanity.com/paper/2104.08697/) (2021)
- [Towards Improving Workers' Safety and Progress Monitoring of Construction Sites Through Construction Site Understanding](https://mlsanity.com/paper/2210.15760/) (2022)
- [Anchor Free remote sensing detector based on solving discrete polar coordinate equation](https://mlsanity.com/paper/2303.11694/) (2023)
- [RMK RetinaNet: Rotated Multi-Kernel RetinaNet for Robust Oriented Object Detection in Remote Sensing Imagery](https://mlsanity.com/paper/2603.04793/) (2026)
- [LOGOS: Language-guided Oriented Object Detection in Aerial Scenes](https://mlsanity.com/paper/2607.08004/) (2026)

## Abstract (arXiv)

Object detection in aerial images is a challenging task due to the lack of visible features and variant orientation of objects. Significant progress has been made recently for predicting targets from aerial images with horizontal bounding boxes (HBBs) and oriented bounding boxes (OBBs) using two-stage detectors with region based convolutional neural networks (R-CNN), involving object localization in one stage and object classification in the other. However, the computational complexity in two-stage detectors is often high, especially for orientational object detection, due to anchor matching and using regions of interest (RoI) pooling for feature extraction. In this paper, we propose a one-stage anchor free detector for orientational object detection, namely, an interactive embranchment network (IENet), which is built upon a detector with prediction in per-pixel fashion. First, a novel geometric transformation is employed to better represent the oriented object in angle prediction, then a branch interactive module with a self-attention mechanism is developed to fuse features from classification and box regression branches. Finally, we introduce an enhanced intersection over union (IoU) loss for OBB detection, which is computationally more efficient than regular polygon IoU. Experiments conducted demonstrate the effectiveness and the superiority of our proposed method, as compared with state-of-the-art detectors.