Comments (3)
dluvizon
commented on July 23, 2024
Hi @Aleberello ,
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We first train the pose model, then we freeze it and train the action part, finally we fine tune the full model (pose+action). For PennAction, training is relatively fast (about one day) and for NTU it takes about 5 days, depending on your computational resources.
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If I understood your statement correctly, yes. We use some samples from PennAction/NTU for first training the pose model because it allows the network to be adapted to these datasets. Although it is not required for the method, it brings small improvements in the final action recognition score.
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Peter654q
commented on July 23, 2024
Hi @dluvizon
May I ask that which GPU you use in this experiments?
Thank you!
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dluvizon
commented on July 23, 2024
Tesla P100 for training, but it should be OK with GTX 1080 Ti too.
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Related Issues (20)
- Testing Script File : Testing script is not Present HOT 1
- Question about action recognition on NTU HOT 11
- Training hyperparameters for train_penn_multimodel.py HOT 2
- Is the model working for multiple person on a crowded scene ? (Not issue) HOT 1
- Weights for predict bboxes on NTU HOT 2
- No weights provided for the multitask models HOT 3
- Questions regarding Pennaction folder HOT 2
- question about displaying output of pose estimation, action recognition HOT 2
- Training on my dataset HOT 1
- could the network be trained with only action video but no pose images/video? HOT 4
- a quick demo for action recognition HOT 4
- something wrong about the eval_penn_multitask.py HOT 2
- eval_penn_ar_pe_merge.py error HOT 1
- Visualization Issue
- ModuleNotFoundError
- Question about datasets and annotations HOT 2
- Training on custom dataset HOT 1
- Error while training penn mpii multimodel HOT 2
- General question with resepect to paper HOT 2
- run.sh is killed HOT 5
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