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Dense Label Encoding for Boundary Discontinuity Free Rotation Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace regression angle prediction with DCL in R3Det | R3Det · DOTA test | mAP50: 76.17 -> 77.37 | Helped |
| Replace regression angle prediction with BCL | RetinaNet · DOTA test | mAP50: 64.17 -> 66.53 | Helped |
| Replace regression angle prediction with GCL | RetinaNet · DOTA test | mAP50: 64.17 -> 66.27 | Helped |
| Replace CSL with BCL | RetinaNet · DOTA test | mAP50: 65.69 -> 66.53 | Helped |
| Add ADARSW (ablation) | RetinaNet-BCL · DOTA test | 10-mAP50: 69.92 -> 72.22 | Helped |
| Add ADARSW (ablation) | RetinaNet-GCL · DOTA test | 10-mAP50: 69.59 -> 71.72 | Helped |
| Set BCL angle granularity to 180/4 (ablation) | RetinaNet-BCL · DOTA val | mAP50:95: 31.49 -> 31.01 | Hurt |
| Set BCL angle granularity to 180/32 (ablation) | RetinaNet-BCL · DOTA val | mAP50:95: 31.49 -> 36.71 | Helped |
| Set BCL angle granularity to 180/512 (ablation) | RetinaNet-BCL · DOTA val | mAP50:95: 31.49 -> 34.99 | Helped |
| Replace regression angle prediction with BCL | RetinaNet · DOTA test | training time: ~3x -> ~1x | Helped |
| Use DCL instead of CSL | RetinaNet · DOTA test | training time: ~3x -> ~1x | Helped |
| Add DCL to R3Det | R3Det · HRSC2016 | mAP (07): 89.26 -> 89.46 | Helped |
Closest papers by meaning
- Rethinking Boundary Discontinuity Problem for Oriented Object Detection (CVPR 2024 · similarity 0.86)
- FRED: Towards a Full Rotation-Equivariance in Aerial Image Object Detection (AAAI 2024 · similarity 0.85)
- ABBSPO: Adaptive Bounding Box Scaling and Symmetric Prior based Orientation Prediction for Detecting Aerial Image Objects (CVPR 2025 · similarity 0.84)
- Multi-clue Consistency Learning to Bridge Gaps Between General and Oriented Object in Semi-supervised Detection (AAAI 2025 · similarity 0.84)
- Selective Disk Bispectrum: A Complete and Rotation Invariant Image Descriptor (NeurIPS 2026 · similarity 0.84)
- Point2RBox: Combine Knowledge from Synthetic Visual Patterns for End-to-end Oriented Object Detection with Single Point Supervision (CVPR 2024 · similarity 0.83)
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