Object Detection In Aerial Images

14 papers with code • 1 benchmarks • 4 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 )

Greatest papers with code

Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges

dingjiansw101/AerialDetection 24 Feb 2021

In this paper, we present a large-scale Dataset of Object deTection in Aerial images (DOTA) and comprehensive baselines for ODAI.

Object Detection In Aerial Images

Learning RoI Transformer for Oriented Object Detection in Aerial Images

dingjiansw101/AerialDetection CVPR 2019

Object detection in aerial images is an active yet challenging task in computer vision because of the bird's-eye view perspective, the highly complex backgrounds, and the variant appearances of objects.

Object Classification Object Detection In Aerial Images

R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object

SJTU-Det/R3Det_Tensorflow 15 Aug 2019

Considering the shortcoming of feature misalignment in existing refined single-stage detector, we design a feature refinement module to improve detection performance by getting more accurate features.

Object Detection In Aerial Images

SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects

yangxue0827/RotationDetection ICCV 2019

Specifically, a sampling fusion network is devised which fuses multi-layer feature with effective anchor sampling, to improve the sensitivity to small objects.

Object Detection In Aerial Images Scene Text

DOTA: A Large-scale Dataset for Object Detection in Aerial Images

CAPTAIN-WHU/DOTA_devkit CVPR 2018

The fully annotated DOTA images contains $188, 282$ instances, each of which is labeled by an arbitrary (8 d. o. f.)

Object Detection In Aerial Images

Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors

yijingru/BBAVectors-Oriented-Object-Detection 17 Aug 2020

To address this issue, in this work we extend the horizontal keypoint-based object detector to the oriented object detection task.

Object Detection In Aerial Images

Align Deep Features for Oriented Object Detection

csuhan/s2anet 21 Aug 2020

However most of existing methods rely on heuristically defined anchors with different scales, angles and aspect ratios and usually suffer from severe misalignment between anchor boxes and axis-aligned convolutional features, which leads to the common inconsistency between the classification score and localization accuracy.

Object Detection In Aerial Images

ReDet: A Rotation-equivariant Detector for Aerial Object Detection

csuhan/ReDet CVPR 2021

More precisely, we incorporate rotation-equivariant networks into the detector to extract rotation-equivariant features, which can accurately predict the orientation and lead to a huge reduction of model size.

Object Detection In Aerial Images

Dynamic Anchor Learning for Arbitrary-Oriented Object Detection

ming71/DAL 8 Dec 2020

With the newly introduced DAL, we achieve superior detection performance for arbitrary-oriented objects with only a few horizontal preset anchors.

 Ranked #1 on 2D Object Detection on DOTA (using extra training data)

Multi-Oriented Scene Text Detection Object Detection In Aerial Images

Learning RoI Transformer for Detecting Oriented Objects in Aerial Images

dingjiansw101/RoITransformer_DOTA 1 Dec 2018

Especially when detecting densely packed objects in aerial images, methods relying on horizontal proposals for common object detection often introduce mismatches between the Region of Interests (RoIs) and objects.

General Classification Object Classification +1