Models: - Name: faster-rcnn_s50_fpn_syncbn-backbone+head_ms-range-1x_coco In Collection: Faster R-CNN Config: configs/resnest/faster-rcnn_s50_fpn_syncbn-backbone+head_ms-range-1x_coco.py Metadata: Training Memory (GB): 4.8 Epochs: 12 Training Data: COCO Training Techniques: - SGD with Momentum - Weight Decay Training Resources: 8x V100 GPUs Architecture: - ResNeSt Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 42.0 Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/faster_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco/faster_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco_20200926_125502-20289c16.pth Paper: URL: https://arxiv.org/abs/2004.08955 Title: 'ResNeSt: Split-Attention Networks' README: configs/resnest/README.md Code: URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273 Version: v2.7.0 - Name: faster-rcnn_s101_fpn_syncbn-backbone+head_ms-range-1x_coco In Collection: Faster R-CNN Config: configs/resnest/faster-rcnn_s101_fpn_syncbn-backbone+head_ms-range-1x_coco.py Metadata: Training Memory (GB): 7.1 Epochs: 12 Training Data: COCO Training Techniques: - SGD with Momentum - Weight Decay Training Resources: 8x V100 GPUs Architecture: - ResNeSt Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 44.5 Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/faster_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco/faster_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco_20201006_021058-421517f1.pth Paper: URL: https://arxiv.org/abs/2004.08955 Title: 'ResNeSt: Split-Attention Networks' README: configs/resnest/README.md Code: URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273 Version: v2.7.0 - Name: mask-rcnn_s50_fpn_syncbn-backbone+head_ms-1x_coco In Collection: Mask R-CNN Config: configs/resnest/mask-rcnn_s50_fpn_syncbn-backbone+head_ms-1x_coco.py Metadata: Training Memory (GB): 5.5 Epochs: 12 Training Data: COCO Training Techniques: - SGD with Momentum - Weight Decay Training Resources: 8x V100 GPUs Architecture: - ResNeSt Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 42.6 - Task: Instance Segmentation Dataset: COCO Metrics: mask AP: 38.1 Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/mask_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco/mask_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco_20200926_125503-8a2c3d47.pth Paper: URL: https://arxiv.org/abs/2004.08955 Title: 'ResNeSt: Split-Attention Networks' README: configs/resnest/README.md Code: URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273 Version: v2.7.0 - Name: mask-rcnn_s101_fpn_syncbn-backbone+head_ms-1x_coco In Collection: Mask R-CNN Config: configs/resnest/mask-rcnn_s101_fpn_syncbn-backbone+head_ms-1x_coco.py Metadata: Training Memory (GB): 7.8 Epochs: 12 Training Data: COCO Training Techniques: - SGD with Momentum - Weight Decay Training Resources: 8x V100 GPUs Architecture: - ResNeSt Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 45.2 - Task: Instance Segmentation Dataset: COCO Metrics: mask AP: 40.2 Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/mask_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco/mask_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco_20201005_215831-af60cdf9.pth Paper: URL: https://arxiv.org/abs/2004.08955 Title: 'ResNeSt: Split-Attention Networks' README: configs/resnest/README.md Code: URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273 Version: v2.7.0 - Name: cascade-rcnn_s50_fpn_syncbn-backbone+head_ms-range-1x_coco In Collection: Cascade R-CNN Config: configs/resnest/cascade-rcnn_s50_fpn_syncbn-backbone+head_ms-range-1x_coco.py Metadata: Epochs: 12 Training Data: COCO Training Techniques: - SGD with Momentum - Weight Decay Training Resources: 8x V100 GPUs Architecture: - ResNeSt Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 44.5 Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/cascade_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco/cascade_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco_20201122_213640-763cc7b5.pth Paper: URL: https://arxiv.org/abs/2004.08955 Title: 'ResNeSt: Split-Attention Networks' README: configs/resnest/README.md Code: URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273 Version: v2.7.0 - Name: cascade-rcnn_s101_fpn_syncbn-backbone+head_ms-range-1x_coco In Collection: Cascade R-CNN Config: configs/resnest/cascade-rcnn_s101_fpn_syncbn-backbone+head_ms-range-1x_coco.py Metadata: Training Memory (GB): 8.4 Epochs: 12 Training Data: COCO Training Techniques: - SGD with Momentum - Weight Decay Training Resources: 8x V100 GPUs Architecture: - ResNeSt Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 46.8 Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/cascade_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco/cascade_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain-range_1x_coco_20201005_113242-b9459f8f.pth Paper: URL: https://arxiv.org/abs/2004.08955 Title: 'ResNeSt: Split-Attention Networks' README: configs/resnest/README.md Code: URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273 Version: v2.7.0 - Name: cascade-mask-rcnn_s50_fpn_syncbn-backbone+head_ms-1x_coco In Collection: Cascade R-CNN Config: configs/resnest/cascade-mask-rcnn_s50_fpn_syncbn-backbone+head_ms-1x_coco.py Metadata: Epochs: 12 Training Data: COCO Training Techniques: - SGD with Momentum - Weight Decay Training Resources: 8x V100 GPUs Architecture: - ResNeSt Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 45.4 - Task: Instance Segmentation Dataset: COCO Metrics: mask AP: 39.5 Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/cascade_mask_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco/cascade_mask_rcnn_s50_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco_20201122_104428-99eca4c7.pth Paper: URL: https://arxiv.org/abs/2004.08955 Title: 'ResNeSt: Split-Attention Networks' README: configs/resnest/README.md Code: URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273 Version: v2.7.0 - Name: cascade-mask-rcnn_s101_fpn_syncbn-backbone+head_ms-1x_coco In Collection: Cascade R-CNN Config: configs/resnest/cascade-mask-rcnn_s101_fpn_syncbn-backbone+head_ms-1x_coco.py Metadata: Training Memory (GB): 10.5 Epochs: 12 Training Data: COCO Training Techniques: - SGD with Momentum - Weight Decay Training Resources: 8x V100 GPUs Architecture: - ResNeSt Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 47.7 - Task: Instance Segmentation Dataset: COCO Metrics: mask AP: 41.4 Weights: https://download.openmmlab.com/mmdetection/v2.0/resnest/cascade_mask_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco/cascade_mask_rcnn_s101_fpn_syncbn-backbone%2Bhead_mstrain_1x_coco_20201005_113243-42607475.pth Paper: URL: https://arxiv.org/abs/2004.08955 Title: 'ResNeSt: Split-Attention Networks' README: configs/resnest/README.md Code: URL: https://github.com/open-mmlab/mmdetection/blob/v2.7.0/mmdet/models/backbones/resnest.py#L273 Version: v2.7.0