Comments (5)
@zronly how were you able to get the results you cited? I'm trying to do the same from my end, but I get mAP @ IoU=0.5 that's extremely low (less than 1%). The classification mAP reaches +90%.
I'm running the ActivityNet1.2 experiment with the following settings:
python main.py --dataset-name ActivityNet1.2 --num-class 100 --model-name AN1.2_reprduce
I edited the smooth() function in detectionMAP.py to include the savgol_filter() call. I have played around with the threshold, but the detection mAP is still extremely low.
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Please refer to this: #7
Also need to use savgol_filter as @HumamAlwassel mentioned.
from wtalc-pytorch.
Please refer to this: #7
Also need to use savgol_filter as @HumamAlwassel mentioned.
Yes, i have used the same setting as what you said, but i find the CASLOSS is not work when training the activitynet1.2 , because when the casloss goes down, the accuracy also goes down. Is this caused by batch size? or learning rate?
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@zronly i have test the results on ActivitNet1.2, and get the same results as yours mAP@0.5=33.5, if you have got the results posted in paper, please let me know.
I run experiments on ActivityNet1.2 with the following settings:
python main.py --dataset-name ActivityNet1.2 --num-class 100
I do not change any other parameters in options.py provided by author used for training thumos14.
@sujoyp I will be really appreciate if you could offer the option.py used for ActivityNet
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@zronly i have test the results on ActivitNet1.2, and get the same results as yours mAP@0.5=33.5, if you have got the results posted in paper, please let me know.
I run experiments on ActivityNet1.2 with the following settings:
python main.py --dataset-name ActivityNet1.2 --num-class 100
I do not change any other parameters in options.py provided by author used for training thumos14.
@sujoyp I will be really appreciate if you could offer the option.py used for ActivityNet
the casloss don't work when training on ActivityNet1.2, i am not sure if it has anything to do with parameters.
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Related Issues (20)
- The model results vary greatly HOT 1
- I believe labels_all.npy is wrong HOT 1
- About Qualitative Results
- difference between labels.npy and labels_all.npy HOT 1
- Both Classification and Localization Performance is higher in my experiment than your eccv18 paper in Thumos14 HOT 4
- How can i extract the feature by myself? HOT 1
- RuntimeError: The size of tensor a (101) must match the size of tensor b (20) at non-singleton dimension 1
- Visualization
- FPS of ActivityNet?
- Could you provide the pre-trained encoder?
- Regarding feature extraction HOT 2
- Can you share the UntrimmedNet feature for ActivityNet1.2
- regarding result
- Specific composition of features HOT 1
- calculate features HOT 13
- features download HOT 4
- training on ActivityNet v1.2 HOT 3
- overfitting HOT 1
- extracted_fps of Thumos14reduced-I3D-JOINTFeatures HOT 3
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