OpenMMLab Detection Toolbox and Benchmark https://mmdetection.readthedocs.io/
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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:
URL: https://arxiv.org/abs/1903.00621
Title: 'Feature Selective Anchor-Free Module for Single-Shot Object Detection'
README: configs/fsaf/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.1.0/mmdet/models/detectors/fsaf.py#L6
Version: v2.1.0
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