## 3 Benchmark
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline  & \multicolumn{6}{c}{**BBRefinement, EfficientNet**} \\ \hline
**Model** & **Source** & **Baseline** & **B0** & **B1** & **B2** & **B3** & **B4** & **Boost** \\ \hline \multicolumn{10}{c}{All objects} \\ \hline Faster R-CNN, ResNet-50 C4 1x & Detectron2 & 35.7 & 37.3 & 37.4 & 37.7 & **37.8** & 37.7 & \(+\)2.1 \\ Faster R-CNN ResNet-101 C4 3x & Detectron2 & 41.1 & 41.6 & 41.6 & 42.0 & **42.1** & 42.0 & \(+\)1.0 \\ Faster R-CNN, ResNeXt-101 FPN 3x & Detectron2 & 43.0 & 43.0 & 43.1 & **43.5** & 43.4 & \(+\)0.5 \\ RetinaNet, ResNet-50 FPN 1x & Detectron2 & 37.4 & 38.2 & 38.3 & **38.6** & **38.6** & \(+\)1.2 \\ RetinaNet, ResNet-101 FPN 3x & Detectron2 & 40.4 & 40.6 & 40.6 & **41.0** & **41.0** & 40.9 & \(+\)0.6 \\ Cascade Mask R-CNN, ResNet-50 & Detectron2 & **42.1** & 41.1 & 41.1 & 41.5 & 41.5 & \(-\)0.6 \\ Mask R-CNN ResNet-50 FPN 1x & Detectron2 & 38.6 & 39.6 & 39.7 & 40.0 & **40.2** & 40.0 & \(+\)1.2 \\ Mask R-CNN ResNeXt-101 FPN 3x & Detectron2 & 44.3 & 44.0 & 44.1 & 44.4 & **44.5** & 44.4 & \(+\)0.2 \\ DETR, ResNet-50 & Standalone & 34.3 & 35.7 & 35.8 & 36.0 & **36.1** & 35.9 & \(+\)1.8 \\ YOLOv3 & MMDetection & 33.5 & 34.3 & 34.4 & 34.6 & **34.7** & 34.5 & \(+\)1.2 \\ SSD 512 & MMDetection & 29.4 & 31.2 & 31.3 & 31.5 & **31.6** & 31.4 & \(+\)2.2 \\ \hline \multicolumn{10}{c}{Small objects} \\ \hline Faster R-CNN, ResNet-50 C4 1x & Detectron2 & 19.2 & 19.2 & **19.3** & 19.1 & 18.9 & \(+\)0.1 \\ Faster R-CNN ResNet-101 C4 3x & Detectron2 & 22.2 & 22.1 & 22.0 & 22.2 & **22.3** & 22.0 & \(+\)0.1 \\ Faster R-CNN, ResNeXt-101 FPN 3x & Detectron2 & **27.2** & 25.9 & 25.8 & 25.7 & 25.8 & 25.6 & \(-\)1.3 \\ RetinaNet, ResNet-50 FPN 1x & Detectron2 & **24.0** & 22.0 & 22.0 & 22.1 & 22.1 & \(-\)1.9 \\ RetinaNet, ResNet-101 FPN 3x & Detectron2 & **24.0** & 23.4 & 23.2 & 23.3 & 23.6 & 23.2 & \(-\)0.4 \\ Cascade Mask R-CNN, ResNet-50 & Detectron2 & **24.3** & 22.6 & 22.4 & 22.5 & 22.6 & 22.5 & \(-\)1.7 \\ Mask R-CNN ResNet-50 FPN 1x & Detectron2 & **22.5** & 21.9 & 21.7 & 21.8 & 22.0 & 21.7 & \(-\)0.5 \\ Mask R-CNN ResNeXt-101 FPN 3x & Detectron2 & **27.5** & 26.4 & 26.1 & 26.2 & 26.3 & 26.2 & \(-\)1.1 \\ DETR, ResNet-50 & Standalone & 14.3 & **16.0** & 15.9 & 15.9 & 15.9 & 15.7 & \(+\)1.7 \\ YOLOv3 & MMDetection & 19.6 & 19.7 & 19.6 & 19.7 & **20.0** & 19.5 & \(+\)0.4 \\ SSD 512 & MMDetection & 11.7 & **12.8** & 12.5 & 12.7 & 12.7 & 12.5 & \(+\)1.1 \\ \hline \multicolumn{10}{c}{Medium objects} \\ \hline Faster R-CNN, ResNet-50 C4 1x & Detectron2 & 40.9 & 42.3 & 42.6 & **42.8** & **42.8** & **42.8** & +1.9 \\ Faster R-CNN ResNet-101 C4 3x & Detectron22 & 45.5 & 46.2 & 46.3 & **46.6** & **46.6** & **46.6** & \(+\)1.1 \\ Faster R-CNN, ResNeXt-101 FPN 3x & Detectron2 & 46.1 & 46.5 & 46.7 & **47.0** & **47.0** & 46.9 & \(+\)0.9 \\ RetinaNet, ResNet-50 FPN 1x & Detectron2 & 41.6 & 42.8 & 42.9 & **43.2** & **43.2** & 43.1 & \(+\)1.6 \\ RetinaNet, ResNet-101 FPN 3x & Detectron2 & 44.3 & 44.8 & 44.9 & **45.3** & 45.2 & 45.0 & \(+\)1.0 \\ Cascade Mask R-CNN, ResNet-50 & Detectron2 & 45.2 & 44.5 & 44.6 & 45.0 & 45.1 & 44.9 & \(-\)0.1 \\ FFN 1x & Detectron2 & 42.0 & 43.3 & 43.4 & **43.8** & **43.7** & \(+\)1.8 \\ Mask R-CNN ResNeXt-101 FPN 3x & Detectron2 & 47.6 & 47.9 & 48.0 & **48.4** & 48.3 & \(+\)0.8 \\ DETR, ResNet-50 & Standalone & 36.6 & 38.5 & 38.6 & 38.8 & **39.0** & 38.8 & \(+\)2.4 \\ YOLOv3 & MMDetection & 36.4 & 38.9 & 39.0 & 39.3 & **39.4** & 39.3 & \(+\)3.0 \\ SSD 512 & MMDetection & 34.1 & 37.3 & 37.4 & **37.7** & **37.7** & 37.5 & \(+\)3.6 \\ \hline \multicolumn{10}{c}{Large objects} \\ \hline Faster R-CNN, ResNet-50 C4 1x & Detectron2 & 48.7 & 52.4 & 52.8 & 53.1 & 53.1 & **53.2** & \(+\)4.5 \\ Faster R-CNN ResNet-101 C4 3x & Detectron2 & 55.9 & 57.2 & 57.3 & 58.0 & 58.0 & **58.1** & \(+\)2.2 \\ Faster R-CNN, ResNeXt-101 FPN 3x & Detectron2 & 54.9 & 56.3 & 56.7 & 57.0 & 57.2 & \(57.2\) & \(+\)2.3 \\ RetinaNet, ResNet-50 FPN 1x & Detectron2 & 48.3 & 50.3 & 50.7 & **51.5** & 51.1 & 51.2 & \(+\)3.2 \\ RetinaNet, ResNet-101 FPN 3x & Detectron2 & 52.2 & 53.6 & 53.7 & 54.2 & 54.1 & \(\mathbf{54.4}\) & \(+\)2.2 \\ Cascade Mask R-CNN, ResNet-50 & Detectron2 & 54.8 & 54.8 & 55.0 & **55.5** & 55.4 & \(+\)0.7 \\ YOLOv3 & MMDetection & 49.9 & 52.8 & 53.1 & 53.4 & **53.7** & 53.6 & \(+\)3.8 \\ Mask R-CNN ResNeXt-101 FPN 3x & Detectron2 & 56.7 & 57.7 & 58.4 & **58.8** & 58.8 & \(+\)2.1 \\ DETR, ResNet-50 & Standalone & 51.5 & 52.1 & 52.3 & **52.7** & **52.7** & 52.6 & \(+\)1.2 \\ YOLOv3 & MMDetection & 43.6 & 44.1 & 44.3 & 44.7 & **44.9** & 44.7 & \(+\)1.3 \\ SSD 512 & MMDetection & 44.9 & 47.0 & 47.2 & 47.7 & **47.8** & 47.4 & \(+\)2.9 \\ \hline \multicolumn{10}{c}{Medium objects} \\ \hline Faster R-CNN, ResNet-50 C4 1x & Detectron2 & 40.9 & 42.3 & 42.6 & **42.8** & **42.8** & **42.8** & +1.9 \\ Faster R-CNN ResNet-101 C4 3x & Detectron22 & 45.5 & 46.2 & 46.3 & **46.6** & **46.6** & **46.