Comments (4)
Both TUM and SFAM are a little complex,it doesn't make sense why this architecture could speed up so fast. Both the hourglass TUM and fully connection attention are not friendly to speed. Wait for the code.
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TUM is a Thinned U-shape Module, it is not as slow as you think. The parameters of A TUM is even less than a Conv layer 1024x3x3x1024.
SFAM is also not as complex. First, concatenation; then implement SE attention for multi-scale features. Only 6 SE attentions. As a comparison, SE-ResNet101 have more and more SE attentions than ResNet101.
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i have tried it in darknet ,and where the network get deeper ,then the network will be slower,
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@leo-XUKANG very interesting try. I am also curious why M2DET will have such fast speed. Would you share your code of M2DET in darknet?
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Related Issues (20)
- I wrote how to run on mac os.
- The test for coco2017 and get mAP 0.0? model is m2det512_vgg.pth
- Someone have test result on VOC2007 ? HOT 5
- train error HOT 5
- 论文中有一处错误
- Are you using batch size 8 for bn update?
- Why adjust_learning_rate() only refers to step_lr of COCO? HOT 1
- can anyone explain what is the loss_L and loss_c in the training results ? HOT 1
- AttributeError: 'CustomDataset' object has no attribute 'evaluate_detections'AttributeError: 'CustomDataset' object has no attribute 'evaluate_detections'
- Two question about upsample process
- error when run demo.py
- RuntimeError: all tensors must be on devices[0] HOT 1
- mAP精度问题
- On which dataset was m2det512_vgg.pth trained?
- Hard Negative Mining problem
- demo | qt.qpa.xcb: could not connect to display HOT 1
- Does anyone have the weight of resnet101 HOT 1
- File "home/CLNet/main.py", line 87, in <module> main () File "home/CLNet/main.py", line 25, in main model = init_model(args) File "/content/drive/My Drive/home/CLNet/utils/init.py", line 51, in init_model model.load_state_dict(state_dict) File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1407, in load_state_dict self.__class__.__name__, "\n\t".join(error_msgs))) RuntimeError: Error(s) in loading state_dict for CLNet: HOT 1
- GFLOPs!!!
- ImportError: /home/wdc/M2Det/utils/nms/gpu_nms.cpython-37m-x86_64-linux-gnu.so: undefined symbol: cudaSetupArgument
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