https://github.com/Totraproducts/AerialObjectDetection
Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges
Papers with Code 아카이브
Object Detection In Aerial Images
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 8
- 보존된 평가 기록
- 89
Object Detection in Aerial Images is the task of detecting objects from aerial images.
<span style="color:grey; opacity: 0.6">( Image credit: DOTA: A Large-Scale Dataset for Object Detection in Aerial Images )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/V3Det/mmdetection-V3Det
RTMDet: An Empirical Study of Designing Real-Time Object Detectors
https://github.com/cameronchoi/r3det-copy
R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
https://github.com/cszzshi/SimD
RTMDet: An Empirical Study of Designing Real-Time Object Detectors
https://github.com/cuzyoung/crossearth
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
https://github.com/dingjiansw101/RoITransformer_DOTA
Learning RoI Transformer for Detecting Oriented Objects in Aerial Images
https://github.com/fyangneil/Clustered-Object-Detection-in-Aerial-Image
https://github.com/gplast/DroNet
DroNet: Efficient convolutional neural network detector for real-time UAV applications
https://github.com/gplast/DroNet_PyTorch
DroNet: Efficient convolutional neural network detector for real-time UAV applications
https://github.com/hukaixuan19970627/yolov5_obb
On the Arbitrary-Oriented Object Detection: Classification based Approaches Revisited
https://github.com/jessemelpolio/Faster_RCNN_for_DOTA
DOTA: A Large-scale Dataset for Object Detection in Aerial Images
https://github.com/jshermeyer/RFSR
https://github.com/kawshik8/DL-project
https://github.com/lwCVer/DecoupleNet
https://github.com/magnificent1208/r3det-on-mmdetection
R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
https://github.com/ming71/UCAS-AOD-benchmark
DOTA: A Large-scale Dataset for Object Detection in Aerial Images
https://github.com/open-edge-platform/geti
RTMDet: An Empirical Study of Designing Real-Time Object Detectors
https://github.com/open-edge-platform/training_extensions
RTMDet: An Empirical Study of Designing Real-Time Object Detectors
https://github.com/open-mmlab/mmrotate
DOTA: A Large-scale Dataset for Object Detection in Aerial Images
https://github.com/open-mmlab/mmyolo
RTMDet: An Empirical Study of Designing Real-Time Object Detectors
https://github.com/pierlj/proto_faster_rcnn
Experience feedback using Representation Learning for Few-Shot Object Detection on Aerial Images
https://github.com/steven-lang/arxiv-downloader
https://github.com/taegoobot/aerial-object-detector
DOTA: A Large-scale Dataset for Object Detection in Aerial Images
https://github.com/ultralytics/xview-yolov3
https://github.com/yuyi1005/point2rbox-mmrotate
RTMDet: An Empirical Study of Designing Real-Time Object Detectors
https://github.com/zhaozeyang108/Oriented-DETR
Projecting Points to Axes: Oriented Object Detection via Point-Axis Representation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.