Oriented Object Detection
47 papers with code • 3 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Oriented Object Detection
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Libraries
Use these libraries to find Oriented Object Detection models and implementations
DOTA
DOTA 2.0
SODA-A
Most implemented papers
RTMDet: An Empirical Study of Designing Real-Time Object Detectors
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.
On the Arbitrary-Oriented Object Detection: Classification based Approaches Revisited
yangxue0827/RotationDetection
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ECCV 2020
For the resulting circularly distributed angle classification problem, we first devise a Circular Smooth Label technique to handle the periodicity of angle and increase the error tolerance to adjacent angles.
Oriented R-CNN for Object Detection
jbwang1997/OBBDetection
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ICCV 2021
Current state-of-the-art two-stage detectors generate oriented proposals through time-consuming schemes.
Align Deep Features for Oriented Object Detection
csuhan/s2anet
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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.
H2RBox: Horizontal Box Annotation is All You Need for Oriented Object Detection
yangxue0827/h2rbox-mmrotate
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Oriented object detection emerges in many applications from aerial images to autonomous driving, while many existing detection benchmarks are annotated with horizontal bounding box only which is also less costive than fine-grained rotated box, leading to a gap between the readily available training corpus and the rising demand for oriented object detection.
Learning RoI Transformer for Oriented Object Detection in Aerial Images
dingjiansw101/AerialDetection
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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.
Dynamic Anchor Learning for Arbitrary-Oriented Object Detection
ming71/DAL
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With the newly introduced DAL, we achieve superior detection performance for arbitrary-oriented objects with only a few horizontal preset anchors.
MODS -- A USV-oriented object detection and obstacle segmentation benchmark
lojzezust/WaSR
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We propose a new obstacle segmentation performance evaluation protocol that reflects the detection accuracy in a way meaningful for practical USV navigation.
Oriented RepPoints for Aerial Object Detection
LiWentomng/OrientedRepPoints
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CVPR 2022
In contrast to the generic object, aerial targets are often non-axis aligned with arbitrary orientations having the cluttered surroundings.
FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection
lzh420202/fcosr
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We convert a lightweight FCOSR model to TensorRT format, which achieves 73. 93 mAP on DOTA1. 0 at a speed of 10. 68 FPS on Jetson Xavier NX with single scale.
