34 lines
1.0 KiB
YAML
34 lines
1.0 KiB
YAML
Collections:
|
|
- Name: AutoAssign
|
|
Metadata:
|
|
Training Data: COCO
|
|
Training Techniques:
|
|
- SGD with Momentum
|
|
- Weight Decay
|
|
Training Resources: 8x V100 GPUs
|
|
Architecture:
|
|
- AutoAssign
|
|
- FPN
|
|
- ResNet
|
|
Paper:
|
|
URL: https://arxiv.org/abs/2007.03496
|
|
Title: 'AutoAssign: Differentiable Label Assignment for Dense Object Detection'
|
|
README: configs/autoassign/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmdetection/blob/v2.12.0/mmdet/models/detectors/autoassign.py#L6
|
|
Version: v2.12.0
|
|
|
|
Models:
|
|
- Name: autoassign_r50_fpn_8x2_1x_coco
|
|
In Collection: AutoAssign
|
|
Config: configs/autoassign/autoassign_r50_fpn_8x2_1x_coco.py
|
|
Metadata:
|
|
Training Memory (GB): 4.08
|
|
Epochs: 12
|
|
Results:
|
|
- Task: Object Detection
|
|
Dataset: COCO
|
|
Metrics:
|
|
box AP: 40.4
|
|
Weights: https://download.openmmlab.com/mmdetection/v2.0/autoassign/auto_assign_r50_fpn_1x_coco/auto_assign_r50_fpn_1x_coco_20210413_115540-5e17991f.pth
|