Object Detection In Aerial Images

52 papers with code • 6 benchmarks • 8 datasets

Object Detection in Aerial Images is the task of detecting objects from aerial images.

( Image credit: DOTA: A Large-Scale Dataset for Object Detection in Aerial Images )

Libraries

Use these libraries to find Object Detection In Aerial Images models and implementations

MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining

vitae-transformer/mtp 20 Mar 2024

However, transferring the pretrained models to downstream tasks may encounter task discrepancy due to their formulation of pretraining as image classification or object discrimination tasks.

33
20 Mar 2024

On the Robustness of Object Detection Models in Aerial Images

hehaodong530/dota-c 29 Aug 2023

The robustness of object detection models is a major concern when applied to real-world scenarios.

20
29 Aug 2023

Spatial Transform Decoupling for Oriented Object Detection

yuhongtian17/spatial-transform-decoupling 21 Aug 2023

Vision Transformers (ViTs) have achieved remarkable success in computer vision tasks.

36
21 Aug 2023

Density Crop-guided Semi-supervised Object Detection in Aerial Images

akhilpm/dronessod 9 Aug 2023

One of the important bottlenecks in training modern object detectors is the need for labeled images where bounding box annotations have to be produced for each object present in the image.

12
09 Aug 2023

A Robust Feature Downsampling Module for Remote Sensing Visual Tasks

lwCVer/RFD IEEE Transactions on Geoscience and Remote Sensing 2023

To address this problem, we propose a new and universal downsampling module named robust feature downsampling (RFD).

8
01 Jun 2023

Large Selective Kernel Network for Remote Sensing Object Detection

zcablii/Large-Selective-Kernel-Network ICCV 2023

To the best of our knowledge, this is the first time that large and selective kernel mechanisms have been explored in the field of remote sensing object detection.

301
16 Mar 2023

Adaptive Rotated Convolution for Rotated Object Detection

LeapLabTHU/ARC ICCV 2023

In our ARC module, the convolution kernels rotate adaptively to extract object features with varying orientations in different images, and an efficient conditional computation mechanism is introduced to accommodate the large orientation variations of objects within an image.

84
14 Mar 2023

RTMDet: An Empirical Study of Designing Real-Time Object Detectors

open-mmlab/mmdetection 14 Dec 2022

In this paper, we aim to design an efficient real-time object detector that exceeds the YOLO series and is easily extensible for many object recognition tasks such as instance segmentation and rotated object detection.

27,462
14 Dec 2022

PP-YOLOE-R: An Efficient Anchor-Free Rotated Object Detector

PaddlePaddle/Paddle 4 Nov 2022

With multi-scale training and testing, PP-YOLOE-R-l and PP-YOLOE-R-x further improve the detection precision to 80. 02 and 80. 73 mAP.

21,517
04 Nov 2022

Task-wise Sampling Convolutions for Arbitrary-Oriented Object Detection in Aerial Images

Shank2358/GGHL 6 Sep 2022

Specifically, sampling positions of the localization convolution in TS-Conv are supervised by the oriented bounding box (OBB) prediction associated with spatial coordinates, while sampling positions and convolutional kernel of the classification convolution are designed to be adaptively adjusted according to different orientations for improving the orientation robustness of features.

610
06 Sep 2022