metafile.yml 3.9 KB

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  1. Collections:
  2. - Name: VFNet
  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. - FPN
  11. - ResNet
  12. - Varifocal Loss
  13. Paper:
  14. URL: https://arxiv.org/abs/2008.13367
  15. Title: 'VarifocalNet: An IoU-aware Dense Object Detector'
  16. README: configs/vfnet/README.md
  17. Code:
  18. URL: https://github.com/open-mmlab/mmdetection/blob/v2.6.0/mmdet/models/detectors/vfnet.py#L6
  19. Version: v2.6.0
  20. Models:
  21. - Name: vfnet_r50_fpn_1x_coco
  22. In Collection: VFNet
  23. Config: configs/vfnet/vfnet_r50_fpn_1x_coco.py
  24. Metadata:
  25. Epochs: 12
  26. Results:
  27. - Task: Object Detection
  28. Dataset: COCO
  29. Metrics:
  30. box AP: 41.6
  31. Weights: https://download.openmmlab.com/mmdetection/v2.0/vfnet/vfnet_r50_fpn_1x_coco/vfnet_r50_fpn_1x_coco_20201027-38db6f58.pth
  32. - Name: vfnet_r50_fpn_ms-2x_coco
  33. In Collection: VFNet
  34. Config: configs/vfnet/vfnet_r50_fpn_ms-2x_coco.py
  35. Metadata:
  36. Epochs: 24
  37. Results:
  38. - Task: Object Detection
  39. Dataset: COCO
  40. Metrics:
  41. box AP: 44.8
  42. Weights: https://download.openmmlab.com/mmdetection/v2.0/vfnet/vfnet_r50_fpn_mstrain_2x_coco/vfnet_r50_fpn_mstrain_2x_coco_20201027-7cc75bd2.pth
  43. - Name: vfnet_r50-mdconv-c3-c5_fpn_ms-2x_coco
  44. In Collection: VFNet
  45. Config: configs/vfnet/vfnet_r50-mdconv-c3-c5_fpn_ms-2x_coco.py
  46. Metadata:
  47. Epochs: 24
  48. Results:
  49. - Task: Object Detection
  50. Dataset: COCO
  51. Metrics:
  52. box AP: 48.0
  53. Weights: https://download.openmmlab.com/mmdetection/v2.0/vfnet/vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco/vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco_20201027pth-6879c318.pth
  54. - Name: vfnet_r101_fpn_1x_coco
  55. In Collection: VFNet
  56. Config: configs/vfnet/vfnet_r101_fpn_1x_coco.py
  57. Metadata:
  58. Epochs: 12
  59. Results:
  60. - Task: Object Detection
  61. Dataset: COCO
  62. Metrics:
  63. box AP: 43.6
  64. Weights: https://download.openmmlab.com/mmdetection/v2.0/vfnet/vfnet_r101_fpn_1x_coco/vfnet_r101_fpn_1x_coco_20201027pth-c831ece7.pth
  65. - Name: vfnet_r101_fpn_ms-2x_coco
  66. In Collection: VFNet
  67. Config: configs/vfnet/vfnet_r101_fpn_ms-2x_coco.py
  68. Metadata:
  69. Epochs: 24
  70. Results:
  71. - Task: Object Detection
  72. Dataset: COCO
  73. Metrics:
  74. box AP: 46.7
  75. Weights: https://download.openmmlab.com/mmdetection/v2.0/vfnet/vfnet_r101_fpn_mstrain_2x_coco/vfnet_r101_fpn_mstrain_2x_coco_20201027pth-4a5d53f1.pth
  76. - Name: vfnet_r101-mdconv-c3-c5_fpn_ms-2x_coco
  77. In Collection: VFNet
  78. Config: configs/vfnet/vfnet_r101-mdconv-c3-c5_fpn_ms-2x_coco.py
  79. Metadata:
  80. Epochs: 24
  81. Results:
  82. - Task: Object Detection
  83. Dataset: COCO
  84. Metrics:
  85. box AP: 49.2
  86. Weights: https://download.openmmlab.com/mmdetection/v2.0/vfnet/vfnet_r101_fpn_mdconv_c3-c5_mstrain_2x_coco/vfnet_r101_fpn_mdconv_c3-c5_mstrain_2x_coco_20201027pth-7729adb5.pth
  87. - Name: vfnet_x101-32x4d-mdconv-c3-c5_fpn_ms-2x_coco
  88. In Collection: VFNet
  89. Config: configs/vfnet/vfnet_x101-32x4d-mdconv-c3-c5_fpn_ms-2x_coco.py
  90. Metadata:
  91. Epochs: 24
  92. Results:
  93. - Task: Object Detection
  94. Dataset: COCO
  95. Metrics:
  96. box AP: 50.0
  97. Weights: https://download.openmmlab.com/mmdetection/v2.0/vfnet/vfnet_x101_32x4d_fpn_mdconv_c3-c5_mstrain_2x_coco/vfnet_x101_32x4d_fpn_mdconv_c3-c5_mstrain_2x_coco_20201027pth-d300a6fc.pth
  98. - Name: vfnet_x101-64x4d-mdconv-c3-c5_fpn_ms-2x_coco
  99. In Collection: VFNet
  100. Config: configs/vfnet/vfnet_x101-64x4d-mdconv-c3-c5_fpn_ms-2x_coco.py
  101. Metadata:
  102. Epochs: 24
  103. Results:
  104. - Task: Object Detection
  105. Dataset: COCO
  106. Metrics:
  107. box AP: 50.8
  108. Weights: https://download.openmmlab.com/mmdetection/v2.0/vfnet/vfnet_x101_64x4d_fpn_mdconv_c3-c5_mstrain_2x_coco/vfnet_x101_64x4d_fpn_mdconv_c3-c5_mstrain_2x_coco_20201027pth-b5f6da5e.pth