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2D Object Detection On Sardet 100K

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box mAP

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이 벤치마크에서 각 모델의 성능 결과

모델 이름
box mAP
Paper TitleRepository
MSFA (F-RCNN+R50)51.1SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detection-
Cascade R-CNN51.1Cascade R-CNN: Delving into High Quality Object Detection-
FCOS49.8FCOS: Fully Convolutional One-Stage Object Detection-
MSFA (F-RCNN+ConvNext-T)54.8SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detection-
DenoDet55.4DenoDet: Attention as Deformable Multi-Subspace Feature Denoising for Target Detection in SAR Images-
Grid RCNN48.8Grid R-CNN-
Sparse R-CNN38.1Sparse R-CNN: End-to-End Object Detection with Learnable Proposals-
SARATR-X-SARATR-X: Toward Building A Foundation Model for SAR Target Recognition-
Deformable DETR50.0Deformable DETR: Deformable Transformers for End-to-End Object Detection-
MSFA (GFL+R50)53.7SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detection-
RetinaNet47.4Focal Loss for Dense Object Detection-
F-RCNN49.0Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks-
MSFA (Deformable DETR)51.3SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detection-
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2D Object Detection On Sardet 100K | SOTA | HyperAI초신경