metafile.yml 1.6 KB

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  1. Collections:
  2. - Name: CrowdDet
  3. Metadata:
  4. Training Data: CrowdHuman
  5. Training Techniques:
  6. - SGD
  7. - EMD Loss
  8. Training Resources: 8x A100 GPUs
  9. Architecture:
  10. - FPN
  11. - RPN
  12. - ResNet
  13. - RoIPool
  14. Paper:
  15. URL: https://arxiv.org/abs/2003.09163
  16. Title: 'Detection in Crowded Scenes: One Proposal, Multiple Predictions'
  17. README: configs/crowddet/README.md
  18. Code:
  19. URL: https://github.com/open-mmlab/mmdetection/blob/v3.0.0rc3/mmdet/models/detectors/crowddet.py
  20. Version: v3.0.0rc3
  21. Models:
  22. - Name: crowddet-rcnn_refine_r50_fpn_8xb2-30e_crowdhuman
  23. In Collection: CrowdDet
  24. Config: configs/crowddet/crowddet-rcnn_refine_r50_fpn_8xb2-30e_crowdhuman.py
  25. Metadata:
  26. Training Memory (GB): 4.8
  27. Epochs: 30
  28. Results:
  29. - Task: Object Detection
  30. Dataset: CrowdHuman
  31. Metrics:
  32. box AP: 90.32
  33. Weights: https://download.openmmlab.com/mmdetection/v3.0/crowddet/crowddet-rcnn_refine_r50_fpn_8xb2-30e_crowdhuman/crowddet-rcnn_refine_r50_fpn_8xb2-30e_crowdhuman_20221024_215917-45602806.pth
  34. - Name: crowddet-rcnn_r50_fpn_8xb2-30e_crowdhuman
  35. In Collection: CrowdDet
  36. Config: configs/crowddet/crowddet-rcnn_r50_fpn_8xb2-30e_crowdhuman.py
  37. Metadata:
  38. Training Memory (GB): 4.4
  39. Epochs: 30
  40. Results:
  41. - Task: Object Detection
  42. Dataset: CrowdHuman
  43. Metrics:
  44. box AP: 90.0
  45. Weights: https://download.openmmlab.com/mmdetection/v3.0/crowddet/crowddet-rcnn_r50_fpn_8xb2-30e_crowdhuman/crowddet-rcnn_r50_fpn_8xb2-30e_crowdhuman_20221023_174954-dc319c2d.pth