| Models: | |
| - Name: faster_rcnn_hrnetv2p_w18_1x_coco | |
| In Collection: Faster R-CNN | |
| Config: configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.py | |
| Metadata: | |
| Training Memory (GB): 6.6 | |
| inference time (ms/im): | |
| - value: 74.63 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 12 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 36.9 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco/faster_rcnn_hrnetv2p_w18_1x_coco_20200130-56651a6d.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: faster_rcnn_hrnetv2p_w18_2x_coco | |
| In Collection: Faster R-CNN | |
| Config: configs/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco.py | |
| Metadata: | |
| Training Memory (GB): 6.6 | |
| inference time (ms/im): | |
| - value: 74.63 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 24 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 38.9 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco/faster_rcnn_hrnetv2p_w18_2x_coco_20200702_085731-a4ec0611.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: faster_rcnn_hrnetv2p_w32_1x_coco | |
| In Collection: Faster R-CNN | |
| Config: configs/hrnet/faster_rcnn_hrnetv2p_w32_1x_coco.py | |
| Metadata: | |
| Training Memory (GB): 9.0 | |
| inference time (ms/im): | |
| - value: 80.65 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 12 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 40.2 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w32_1x_coco/faster_rcnn_hrnetv2p_w32_1x_coco_20200130-6e286425.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: faster_rcnn_hrnetv2p_w32_2x_coco | |
| In Collection: Faster R-CNN | |
| Config: configs/hrnet/faster_rcnn_hrnetv2p_w32_2x_coco.py | |
| Metadata: | |
| Training Memory (GB): 9.0 | |
| inference time (ms/im): | |
| - value: 80.65 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 24 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 41.4 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w32_2x_coco/faster_rcnn_hrnetv2p_w32_2x_coco_20200529_015927-976a9c15.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: faster_rcnn_hrnetv2p_w40_1x_coco | |
| In Collection: Faster R-CNN | |
| Config: configs/hrnet/faster_rcnn_hrnetv2p_w40_1x_coco.py | |
| Metadata: | |
| Training Memory (GB): 10.4 | |
| inference time (ms/im): | |
| - value: 95.24 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 12 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 41.2 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w40_1x_coco/faster_rcnn_hrnetv2p_w40_1x_coco_20200210-95c1f5ce.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: faster_rcnn_hrnetv2p_w40_2x_coco | |
| In Collection: Faster R-CNN | |
| Config: configs/hrnet/faster_rcnn_hrnetv2p_w40_2x_coco.py | |
| Metadata: | |
| Training Memory (GB): 10.4 | |
| inference time (ms/im): | |
| - value: 95.24 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 24 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 42.1 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/faster_rcnn_hrnetv2p_w40_2x_coco/faster_rcnn_hrnetv2p_w40_2x_coco_20200512_161033-0f236ef4.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: mask_rcnn_hrnetv2p_w18_1x_coco | |
| In Collection: Mask R-CNN | |
| Config: configs/hrnet/mask_rcnn_hrnetv2p_w18_1x_coco.py | |
| Metadata: | |
| Training Memory (GB): 7.0 | |
| inference time (ms/im): | |
| - value: 85.47 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 12 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 37.7 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 34.2 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w18_1x_coco/mask_rcnn_hrnetv2p_w18_1x_coco_20200205-1c3d78ed.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: mask_rcnn_hrnetv2p_w18_2x_coco | |
| In Collection: Mask R-CNN | |
| Config: configs/hrnet/mask_rcnn_hrnetv2p_w18_2x_coco.py | |
| Metadata: | |
| Training Memory (GB): 7.0 | |
| inference time (ms/im): | |
| - value: 85.47 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 24 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 39.8 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 36.0 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w18_2x_coco/mask_rcnn_hrnetv2p_w18_2x_coco_20200212-b3c825b1.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: mask_rcnn_hrnetv2p_w32_1x_coco | |
| In Collection: Mask R-CNN | |
| Config: configs/hrnet/mask_rcnn_hrnetv2p_w32_1x_coco.py | |
| Metadata: | |
| Training Memory (GB): 9.4 | |
| inference time (ms/im): | |
| - value: 88.5 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 12 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 41.2 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 37.1 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w32_1x_coco/mask_rcnn_hrnetv2p_w32_1x_coco_20200207-b29f616e.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: mask_rcnn_hrnetv2p_w32_2x_coco | |
| In Collection: Mask R-CNN | |
| Config: configs/hrnet/mask_rcnn_hrnetv2p_w32_2x_coco.py | |
| Metadata: | |
| Training Memory (GB): 9.4 | |
| inference time (ms/im): | |
| - value: 88.5 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 24 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 42.5 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 37.8 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w32_2x_coco/mask_rcnn_hrnetv2p_w32_2x_coco_20200213-45b75b4d.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: mask_rcnn_hrnetv2p_w40_1x_coco | |
| In Collection: Mask R-CNN | |
| Config: configs/hrnet/mask_rcnn_hrnetv2p_w40_1x_coco.py | |
| Metadata: | |
| Training Memory (GB): 10.9 | |
| Epochs: 12 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 42.1 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 37.5 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w40_1x_coco/mask_rcnn_hrnetv2p_w40_1x_coco_20200511_015646-66738b35.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: mask_rcnn_hrnetv2p_w40_2x_coco | |
| In Collection: Mask R-CNN | |
| Config: configs/hrnet/mask_rcnn_hrnetv2p_w40_2x_coco.py | |
| Metadata: | |
| Training Memory (GB): 10.9 | |
| Epochs: 24 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 42.8 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 38.2 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/mask_rcnn_hrnetv2p_w40_2x_coco/mask_rcnn_hrnetv2p_w40_2x_coco_20200512_163732-aed5e4ab.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: cascade_rcnn_hrnetv2p_w18_20e_coco | |
| In Collection: Cascade R-CNN | |
| Config: configs/hrnet/cascade_rcnn_hrnetv2p_w18_20e_coco.py | |
| Metadata: | |
| Training Memory (GB): 7.0 | |
| inference time (ms/im): | |
| - value: 90.91 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 20 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 41.2 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_rcnn_hrnetv2p_w18_20e_coco/cascade_rcnn_hrnetv2p_w18_20e_coco_20200210-434be9d7.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: cascade_rcnn_hrnetv2p_w32_20e_coco | |
| In Collection: Cascade R-CNN | |
| Config: configs/hrnet/cascade_rcnn_hrnetv2p_w32_20e_coco.py | |
| Metadata: | |
| Training Memory (GB): 9.4 | |
| inference time (ms/im): | |
| - value: 90.91 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 20 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 43.3 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_rcnn_hrnetv2p_w32_20e_coco/cascade_rcnn_hrnetv2p_w32_20e_coco_20200208-928455a4.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: cascade_rcnn_hrnetv2p_w40_20e_coco | |
| In Collection: Cascade R-CNN | |
| Config: configs/hrnet/cascade_rcnn_hrnetv2p_w40_20e_coco.py | |
| Metadata: | |
| Training Memory (GB): 10.8 | |
| Epochs: 20 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 43.8 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_rcnn_hrnetv2p_w40_20e_coco/cascade_rcnn_hrnetv2p_w40_20e_coco_20200512_161112-75e47b04.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: cascade_mask_rcnn_hrnetv2p_w18_20e_coco | |
| In Collection: Cascade R-CNN | |
| Config: configs/hrnet/cascade_mask_rcnn_hrnetv2p_w18_20e_coco.py | |
| Metadata: | |
| Training Memory (GB): 8.5 | |
| inference time (ms/im): | |
| - value: 117.65 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 20 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 41.6 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 36.4 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_mask_rcnn_hrnetv2p_w18_20e_coco/cascade_mask_rcnn_hrnetv2p_w18_20e_coco_20200210-b543cd2b.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: cascade_mask_rcnn_hrnetv2p_w32_20e_coco | |
| In Collection: Cascade R-CNN | |
| Config: configs/hrnet/cascade_mask_rcnn_hrnetv2p_w32_20e_coco.py | |
| Metadata: | |
| inference time (ms/im): | |
| - value: 120.48 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 20 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 44.3 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 38.6 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_mask_rcnn_hrnetv2p_w32_20e_coco/cascade_mask_rcnn_hrnetv2p_w32_20e_coco_20200512_154043-39d9cf7b.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: cascade_mask_rcnn_hrnetv2p_w40_20e_coco | |
| In Collection: Cascade R-CNN | |
| Config: configs/hrnet/cascade_mask_rcnn_hrnetv2p_w40_20e_coco.py | |
| Metadata: | |
| Training Memory (GB): 12.5 | |
| Epochs: 20 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 45.1 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 39.3 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/cascade_mask_rcnn_hrnetv2p_w40_20e_coco/cascade_mask_rcnn_hrnetv2p_w40_20e_coco_20200527_204922-969c4610.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: htc_hrnetv2p_w18_20e_coco | |
| In Collection: HTC | |
| Config: configs/hrnet/htc_hrnetv2p_w18_20e_coco.py | |
| Metadata: | |
| Training Memory (GB): 10.8 | |
| inference time (ms/im): | |
| - value: 212.77 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 20 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 42.8 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 37.9 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/htc_hrnetv2p_w18_20e_coco/htc_hrnetv2p_w18_20e_coco_20200210-b266988c.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: htc_hrnetv2p_w32_20e_coco | |
| In Collection: HTC | |
| Config: configs/hrnet/htc_hrnetv2p_w32_20e_coco.py | |
| Metadata: | |
| Training Memory (GB): 13.1 | |
| inference time (ms/im): | |
| - value: 204.08 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 20 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 45.4 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 39.9 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/htc_hrnetv2p_w32_20e_coco/htc_hrnetv2p_w32_20e_coco_20200207-7639fa12.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: htc_hrnetv2p_w40_20e_coco | |
| In Collection: HTC | |
| Config: configs/hrnet/htc_hrnetv2p_w40_20e_coco.py | |
| Metadata: | |
| Training Memory (GB): 14.6 | |
| Epochs: 20 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Training Resources: 8x V100 GPUs | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 46.4 | |
| - Task: Instance Segmentation | |
| Dataset: COCO | |
| Metrics: | |
| mask AP: 40.8 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/htc_hrnetv2p_w40_20e_coco/htc_hrnetv2p_w40_20e_coco_20200529_183411-417c4d5b.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: fcos_hrnetv2p_w18_gn-head_4x4_1x_coco | |
| In Collection: FCOS | |
| Config: configs/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_1x_coco.py | |
| Metadata: | |
| Training Resources: 4x V100 GPUs | |
| Batch Size: 16 | |
| Training Memory (GB): 13.0 | |
| inference time (ms/im): | |
| - value: 77.52 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 12 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 35.3 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_1x_coco/fcos_hrnetv2p_w18_gn-head_4x4_1x_coco_20201212_100710-4ad151de.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: fcos_hrnetv2p_w18_gn-head_4x4_2x_coco | |
| In Collection: FCOS | |
| Config: configs/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_2x_coco.py | |
| Metadata: | |
| Training Resources: 4x V100 GPUs | |
| Batch Size: 16 | |
| Training Memory (GB): 13.0 | |
| inference time (ms/im): | |
| - value: 77.52 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 24 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 38.2 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w18_gn-head_4x4_2x_coco/fcos_hrnetv2p_w18_gn-head_4x4_2x_coco_20201212_101110-5c575fa5.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: fcos_hrnetv2p_w32_gn-head_4x4_1x_coco | |
| In Collection: FCOS | |
| Config: configs/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_1x_coco.py | |
| Metadata: | |
| Training Resources: 4x V100 GPUs | |
| Batch Size: 16 | |
| Training Memory (GB): 17.5 | |
| inference time (ms/im): | |
| - value: 77.52 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 12 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 39.5 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_1x_coco/fcos_hrnetv2p_w32_gn-head_4x4_1x_coco_20201211_134730-cb8055c0.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: fcos_hrnetv2p_w32_gn-head_4x4_2x_coco | |
| In Collection: FCOS | |
| Config: configs/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_2x_coco.py | |
| Metadata: | |
| Training Resources: 4x V100 GPUs | |
| Batch Size: 16 | |
| Training Memory (GB): 17.5 | |
| inference time (ms/im): | |
| - value: 77.52 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 24 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 40.8 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w32_gn-head_4x4_2x_coco/fcos_hrnetv2p_w32_gn-head_4x4_2x_coco_20201212_112133-77b6b9bb.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco | |
| In Collection: FCOS | |
| Config: configs/hrnet/fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco.py | |
| Metadata: | |
| Training Resources: 4x V100 GPUs | |
| Batch Size: 16 | |
| Training Memory (GB): 13.0 | |
| inference time (ms/im): | |
| - value: 77.52 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 24 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 38.3 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco/fcos_hrnetv2p_w18_gn-head_mstrain_640-800_4x4_2x_coco_20201212_111651-441e9d9f.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco | |
| In Collection: FCOS | |
| Config: configs/hrnet/fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco.py | |
| Metadata: | |
| Training Resources: 4x V100 GPUs | |
| Batch Size: 16 | |
| Training Memory (GB): 17.5 | |
| inference time (ms/im): | |
| - value: 80.65 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 24 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 41.9 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco/fcos_hrnetv2p_w32_gn-head_mstrain_640-800_4x4_2x_coco_20201212_090846-b6f2b49f.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |
| - Name: fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco | |
| In Collection: FCOS | |
| Config: configs/hrnet/fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco.py | |
| Metadata: | |
| Training Resources: 4x V100 GPUs | |
| Batch Size: 16 | |
| Training Memory (GB): 20.3 | |
| inference time (ms/im): | |
| - value: 92.59 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (800, 1333) | |
| Epochs: 24 | |
| Training Data: COCO | |
| Training Techniques: | |
| - SGD with Momentum | |
| - Weight Decay | |
| Architecture: | |
| - HRNet | |
| Results: | |
| - Task: Object Detection | |
| Dataset: COCO | |
| Metrics: | |
| box AP: 42.7 | |
| Weights: https://download.openmmlab.com/mmdetection/v2.0/hrnet/fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco/fcos_hrnetv2p_w40_gn-head_mstrain_640-800_4x4_2x_coco_20201212_124752-f22d2ce5.pth | |
| Paper: | |
| URL: https://arxiv.org/abs/1904.04514 | |
| Title: 'Deep High-Resolution Representation Learning for Visual Recognition' | |
| README: configs/hrnet/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/backbones/hrnet.py#L195 | |
| Version: v2.0.0 | |