metafile.yml 3.5 KB

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  1. Collections:
  2. - Name: DetectoRS
  3. Metadata:
  4. Training Data: COCO
  5. Training Techniques:
  6. - SGD with Momentum
  7. - Weight Decay
  8. Training Resources: 8x V100 GPUs
  9. Architecture:
  10. - ASPP
  11. - FPN
  12. - RFP
  13. - RPN
  14. - ResNet
  15. - RoIAlign
  16. - SAC
  17. Paper:
  18. URL: https://arxiv.org/abs/2006.02334
  19. Title: 'DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution'
  20. README: configs/detectors/README.md
  21. Code:
  22. URL: https://github.com/open-mmlab/mmdetection/blob/v2.2.0/mmdet/models/backbones/detectors_resnet.py#L205
  23. Version: v2.2.0
  24. Models:
  25. - Name: cascade-rcnn_r50-rfp_1x_coco
  26. In Collection: DetectoRS
  27. Config: configs/detectors/cascade-rcnn_r50-rfp_1x_coco.py
  28. Metadata:
  29. Training Memory (GB): 7.5
  30. Epochs: 12
  31. Results:
  32. - Task: Object Detection
  33. Dataset: COCO
  34. Metrics:
  35. box AP: 44.8
  36. Weights: https://download.openmmlab.com/mmdetection/v2.0/detectors/cascade_rcnn_r50_rfp_1x_coco/cascade_rcnn_r50_rfp_1x_coco-8cf51bfd.pth
  37. - Name: cascade-rcnn_r50-sac_1x_coco
  38. In Collection: DetectoRS
  39. Config: configs/detectors/cascade-rcnn_r50-sac_1x_coco.py
  40. Metadata:
  41. Training Memory (GB): 5.6
  42. Epochs: 12
  43. Results:
  44. - Task: Object Detection
  45. Dataset: COCO
  46. Metrics:
  47. box AP: 45.0
  48. Weights: https://download.openmmlab.com/mmdetection/v2.0/detectors/cascade_rcnn_r50_sac_1x_coco/cascade_rcnn_r50_sac_1x_coco-24bfda62.pth
  49. - Name: detectors_cascade-rcnn_r50_1x_coco
  50. In Collection: DetectoRS
  51. Config: configs/detectors/detectors_cascade-rcnn_r50_1x_coco.py
  52. Metadata:
  53. Training Memory (GB): 9.9
  54. Epochs: 12
  55. Results:
  56. - Task: Object Detection
  57. Dataset: COCO
  58. Metrics:
  59. box AP: 47.4
  60. Weights: https://download.openmmlab.com/mmdetection/v2.0/detectors/detectors_cascade_rcnn_r50_1x_coco/detectors_cascade_rcnn_r50_1x_coco-32a10ba0.pth
  61. - Name: htc_r50-rfp_1x_coco
  62. In Collection: DetectoRS
  63. Config: configs/detectors/htc_r50-rfp_1x_coco.py
  64. Metadata:
  65. Training Memory (GB): 11.2
  66. Epochs: 12
  67. Results:
  68. - Task: Object Detection
  69. Dataset: COCO
  70. Metrics:
  71. box AP: 46.6
  72. - Task: Instance Segmentation
  73. Dataset: COCO
  74. Metrics:
  75. mask AP: 40.9
  76. Weights: https://download.openmmlab.com/mmdetection/v2.0/detectors/htc_r50_rfp_1x_coco/htc_r50_rfp_1x_coco-8ff87c51.pth
  77. - Name: htc_r50-sac_1x_coco
  78. In Collection: DetectoRS
  79. Config: configs/detectors/htc_r50-sac_1x_coco.py
  80. Metadata:
  81. Training Memory (GB): 9.3
  82. Epochs: 12
  83. Results:
  84. - Task: Object Detection
  85. Dataset: COCO
  86. Metrics:
  87. box AP: 46.4
  88. - Task: Instance Segmentation
  89. Dataset: COCO
  90. Metrics:
  91. mask AP: 40.9
  92. Weights: https://download.openmmlab.com/mmdetection/v2.0/detectors/htc_r50_sac_1x_coco/htc_r50_sac_1x_coco-bfa60c54.pth
  93. - Name: detectors_htc-r50_1x_coco
  94. In Collection: DetectoRS
  95. Config: configs/detectors/detectors_htc-r50_1x_coco.py
  96. Metadata:
  97. Training Memory (GB): 13.6
  98. Epochs: 12
  99. Results:
  100. - Task: Object Detection
  101. Dataset: COCO
  102. Metrics:
  103. box AP: 49.1
  104. - Task: Instance Segmentation
  105. Dataset: COCO
  106. Metrics:
  107. mask AP: 42.6
  108. Weights: https://download.openmmlab.com/mmdetection/v2.0/detectors/detectors_htc_r50_1x_coco/detectors_htc_r50_1x_coco-329b1453.pth