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Collections:
- Name: ATSS
Metadata:
Training Data: COCO
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- ATSS
- FPN
- ResNet
Paper:
URL: https://arxiv.org/abs/1912.02424
Title: 'Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection'
README: configs/atss/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.0.0/mmdet/models/detectors/atss.py#L6
Version: v2.0.0
Models:
- Name: atss_r50_fpn_1x_coco
In Collection: ATSS
Config: configs/atss/atss_r50_fpn_1x_coco.py
Metadata:
Training Memory (GB): 3.7
inference time (ms/im):
- value: 50.76
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 39.4
Weights: https://download.openmmlab.com/mmdetection/v2.0/atss/atss_r50_fpn_1x_coco/atss_r50_fpn_1x_coco_20200209-985f7bd0.pth
- Name: atss_r101_fpn_1x_coco
In Collection: ATSS
Config: configs/atss/atss_r101_fpn_1x_coco.py
Metadata:
Training Memory (GB): 5.6
inference time (ms/im):
- value: 81.3
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (800, 1333)
Epochs: 12
Results:
- Task: Object Detection
Dataset: COCO
Metrics:
box AP: 41.5
Weights: https://download.openmmlab.com/mmdetection/v2.0/atss/atss_r101_fpn_1x_coco/atss_r101_fpn_1x_20200825-dfcadd6f.pth