Object Detection on DIOR-H (test)
83.1AP50SLIP-RS*
Evaluation results
| Method | Links | |
|---|---|---|
| SLIP-RS*Backbone=ConvNeXT-L, Training data=RS-Attribute-15M, Evaluation Protocol=Fine-tune2026.05 | 83.1 | |
| SLIP-RSBackbone=ConvNeXT-T, Training data=RS-O + RS-C, Evaluation Protocol=Fine-tune2026.05 | 79.97 | |
| SLIP-RS*Backbone=ConvNeXT-T, Training data=RS-Attribute-15M, Evaluation Protocol=Fine-tune2026.05 | 79.94 | |
| ViTPBackbone=ViT-L (Dosovitskiy, 2020), Training data=DIOR, Evaluation Protocol=Fine-tune2026.05 | 79.8 | |
| OpenRSDBackbone=RTMDet-L, Training data=ORSD+, Evaluation Protocol=Fine-tune2026.05 | 76.7 | |
| RTMDetBackbone=RTMDet-L (Lyu et al., 2022), Training data=DOTA2.0 & DIOR, Evaluation Protocol=Fine-tune2026.05 | 76.52 | |
| SLIP-RSBackbone=ConvNeXT-T, Training data=RS-O, Evaluation Protocol=Fine-tune2026.05 | 76.1 | |
| LAE-DINOBackbone=Swin-T, Training data=LAE-1M, Evaluation Protocol=Fine-tune2026.05 | 75.67 | |
| Faster-RCNNBackbone=ConvNeXT-T (Liu et al., 2022), Training data=DOTA2.0 & DIOR, Evaluation Protocol=Fine-tune2026.05 | 74.1 | |
| DINOBackbone=Swin-T (Liu et al., 2021), Training data=DOTA2.0 & DIOR, Evaluation Protocol=Fine-tune2026.05 | 73.27 |