Collections: - Name: FSAF Metadata: Training Data: COCO Training Techniques: - SGD with Momentum - Weight Decay Training Resources: 8x Titan-XP GPUs Architecture: - FPN - FSAF - ResNet Paper: https://arxiv.org/abs/1903.00621 README: configs/fsaf/README.md Models: - Name: fsaf_r50_fpn_1x_coco In Collection: FSAF Config: configs/fsaf/fsaf_r50_fpn_1x_coco.py Metadata: Training Memory (GB): 3.15 inference time (ms/im): - value: 76.92 hardware: V100 backend: PyTorch batch size: 1 mode: FP32 resolution: (800, 1333) Epochs: 12 Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 37.4 Weights: https://download.openmmlab.com/mmdetection/v2.0/fsaf/fsaf_r50_fpn_1x_coco/fsaf_r50_fpn_1x_coco-94ccc51f.pth - Name: fsaf_r101_fpn_1x_coco In Collection: FSAF Config: configs/fsaf/fsaf_r101_fpn_1x_coco.py Metadata: Training Memory (GB): 5.08 inference time (ms/im): - value: 92.59 hardware: V100 backend: PyTorch batch size: 1 mode: FP32 resolution: (800, 1333) Epochs: 12 Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 39.3 (37.9) Weights: https://download.openmmlab.com/mmdetection/v2.0/fsaf/fsaf_r101_fpn_1x_coco/fsaf_r101_fpn_1x_coco-9e71098f.pth - Name: fsaf_x101_64x4d_fpn_1x_coco In Collection: FSAF Config: configs/fsaf/fsaf_x101_64x4d_fpn_1x_coco.py Metadata: Training Memory (GB): 9.38 inference time (ms/im): - value: 178.57 hardware: V100 backend: PyTorch batch size: 1 mode: FP32 resolution: (800, 1333) Epochs: 12 Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 42.4 (41.0) Weights: https://download.openmmlab.com/mmdetection/v2.0/fsaf/fsaf_x101_64x4d_fpn_1x_coco/fsaf_x101_64x4d_fpn_1x_coco-e3f6e6fd.pth