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Models/Strip R-CNN

Strip R-CNN

Reported on 10 benchmarks across 5 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology8 results

3DonHRSC2016
mAP-07· uses extra data· 2025-01-07
90.6
best: 90.89 (CDLA-HOP)
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection arXiv:2501.03775
3DonHRSC2016
mAP-12· uses extra data· 2025-01-07
98.7
best: 98.77 (CDLA-HOP)
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection arXiv:2501.03775
2D ClassificationonHRSC2016
mAP-07· uses extra data· 2025-01-07
90.6
best: 90.89 (CDLA-HOP)
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection arXiv:2501.03775
2D ClassificationonHRSC2016
mAP-12· uses extra data· 2025-01-07
98.7
best: 98.77 (CDLA-HOP)
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection arXiv:2501.03775
2D Object DetectiononHRSC2016
mAP-07· uses extra data· 2025-01-07
90.6
best: 90.89 (CDLA-HOP)
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection arXiv:2501.03775
2D Object DetectiononHRSC2016
mAP-12· uses extra data· 2025-01-07
98.7
best: 98.77 (CDLA-HOP)
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection arXiv:2501.03775
16konHRSC2016
mAP-07· uses extra data· 2025-01-07
90.6
best: 90.89 (CDLA-HOP)
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection arXiv:2501.03775
16konHRSC2016
mAP-12· uses extra data· 2025-01-07
98.7
best: 98.77 (CDLA-HOP)
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection arXiv:2501.03775

Computer Vision2 results

Object DetectiononHRSC2016
mAP-07· uses extra data· 2025-01-07
90.6
best: 90.89 (CDLA-HOP)
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection arXiv:2501.03775
Object DetectiononHRSC2016
mAP-12· uses extra data· 2025-01-07
98.7
best: 98.77 (CDLA-HOP)
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection arXiv:2501.03775