| dichotomous-image-segmentation-on-dis-te1 | HRNet | #11 | max F-Measure: 0.668weighted F-measure: 0.579MAE: 0.088… |
| dichotomous-image-segmentation-on-dis-te2 | HRNet | #10 | max F-Measure: 0.747weighted F-measure: 0.664MAE: 0.087… |
| dichotomous-image-segmentation-on-dis-te3 | HRNet | #10 | max F-Measure: 0.784weighted F-measure: 0.700MAE: 0.080… |
| dichotomous-image-segmentation-on-dis-te4 | HRNet | #10 | max F-Measure: 0.772weighted F-measure: 0.687MAE: 0.092… |
| dichotomous-image-segmentation-on-dis-vd | HRNet | #12 | max F-Measure: 0.726weighted F-measure: 0.641MAE: 0.095… |
| face-alignment-on-300w | HRNet | #16 | NME_inter-ocular (%, Full): 3.32NME_inter-ocular (%, Common): 2.87… |
| face-alignment-on-cofw | HRNet | #8 | NME (inter-ocular): 3.45 |
| face-alignment-on-cofw-68 | HRNetV2-W18 | #6 | NME (inter-ocular): 5.06 |
| face-alignment-on-wflw | HRNet | #13 | NME (inter-ocular): 4.60 |
| instance-segmentation-on-bdd100k-val | HRNet | #2 | AP: 22.5 |
| instance-segmentation-on-coco-minival | HTC (HRNetV2p-W48) | #66 | mask AP: 41.0 |
| object-detection-on-coco | HTC (HRNetV2p-W48) | #118 | box mAP: 47.3AP50: 65.9AP75: 51.2APS: 28.0APM: 49.7APL: 59.8… |
| object-detection-on-coco | Mask R-CNN (HRNetV2p-W48 + cascade) | #130 | box mAP: 46.1AP50: 64.0AP75: 50.3APS: 27.1APM: 48.6APL: 58.3… |
| object-detection-on-coco | CenterNet (HRNetV2-W48) | #154 | box mAP: 43.5AP75: 46.5APS: 22.2APL: 57.8Hardware Burden: 16G… |
| object-detection-on-coco | Faster R-CNN (HRNetV2p-W48) | #170 | box mAP: 42.4AP50: 63.6AP75: 46.4APS: 24.9APM: 44.6APL: 53.0… |
| object-detection-on-coco | FCOS (HRNetV2p-W48) | #189 | box mAP: 40.5AP50: 59.3APS: 23.4APM: 42.6APL: 51.0… |
| object-detection-on-coco-minival | HTC (HRNetV2p-W48) | #99 | box AP: 47.0APS: 28.8APM: 50.3APL: 62.2 |
| object-detection-on-coco-minival | Mask R-CNN (HRNetV2p-W48, cascade) | #109 | box AP: 46.0APS: 27.5APL: 60.1 |
| object-detection-on-coco-minival | HTC (HRNetV2p-W32) | #114 | box AP: 45.3APS: 27.0APM: 48.4APL: 59.5 |
| object-detection-on-coco-minival | Cascade R-CNN (HRNetV2p-W48) | #125 | box AP: 44.6AP50: 62.7AP75: 48.7APS: 26.3APM: 48.1APL: 58.5 |
| object-detection-on-coco-minival | Cascade R-CNN (HRNetV2p-W32) | #137 | box AP: 43.7AP50: 61.7AP75: 47.7APS: 25.6APM: 46.5APL: 57.4 |
| object-detection-on-coco-minival | HTC (HRNetV2p-W18) | #146 | box AP: 43.1APS: 26.6APM: 46.0 |
| object-detection-on-coco-minival | Mask R-CNN (HRNetV2p-W32) | #154 | box AP: 42.3APS: 25.0APM: 45.4 |
| object-detection-on-coco-minival | Faster R-CNN (HRNetV2p-W48) | #159 | box AP: 41.8AP50: 62.8AP75: 45.9APM: 44.7APL: 54.6 |
| object-detection-on-coco-minival | Cascade R-CNN (HRNetV2p-W18) | #166 | box AP: 41.3AP50: 59.2AP75: 44.9APS: 23.7APM: 44.2APL: 54.1 |
| object-detection-on-coco-minival | Faster R-CNN (HRNetV2p-W32) | #169 | box AP: 40.9AP50: 61.8AP75: 44.8APS: 24.4APM: 43.7APL: 53.3 |
| object-detection-on-coco-minival | Mask R-CNN (HRNetV2p-W18) | #189 | box AP: 39.2APM: 41.7APL: 51.0 |
| object-detection-on-coco-minival | Faster R-CNN (HRNetV2p-W18) | #199 | box AP: 38.0AP50: 58.9AP75: 41.5APS: 22.6APM: 40.8APL: 49.6 |
| object-detection-on-coco-minival | Mask R-CNN (HRNetV2p-W32, cascade) | #217 | APS: 26.1APM: 47.9 |
| semantic-segmentation-on-cityscapes | HRNetV2 (train+val) | #35 | Mean IoU (class): 81.6% |
| semantic-segmentation-on-cityscapes-val | HRNetV2 (HRNetV2-W48) | #41 | mIoU: 81.1 |
| semantic-segmentation-on-cityscapes-val | HRNetV2 (HRNetV2-W40) | #51 | mIoU: 80.2 |
| semantic-segmentation-on-dada-seg | HRNet (ACDC) | #9 | mIoU: 27.5 |
| semantic-segmentation-on-pascal-context | CFNet (ResNet-101) | #30 | mIoU: 54.0 |
| semantic-segmentation-on-pascal-context | HRNetV2 HRNetV2-W48 | #31 | mIoU: 54 |
| semantic-segmentation-on-vaihingen | HRNet-48 | #7 | mIoU: 76.75 |
| semantic-segmentation-on-vaihingen | HRNet-18 | #9 | mIoU: 75.90 |
| thermal-image-segmentation-on-mfn-dataset | HRNet | #31 | mIOU: 51.7 |