Comments (3)
Yes, that is enough, should take less than two days.
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Thanks.
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Hi @salmedina , @stephencheung16 and @joaoluiscarreira . I am trying to replicate the experiment of finetuning i3d trained on Kinetics, for ucf-101, as per the methods specified in the paper, but getting unsuccessful in achieving any significant accuracy (not even on training data) even after several iterations. Could you please give any guidance?
To simplify, I just used 10 classes from ucf-101,
extracted 64 contiguous frames from each video, from any (feasible) random begin point for each epoch,
randomly spatially cropped 224x224 from video resized to 256 for each epoch,
used Adam optimiser with initial learning rate(1e-4),
and mean subtarction and division by 255 from data.
I have a M2000 GPU.
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Related Issues (20)
- Optical flow rescaling HOT 5
- How to create a custom action recognition model HOT 2
- Inflating pre-trained models HOT 1
- Trying to create frozen graph, so i can convert it into tflite for android
- Training with different architectures
- customize actions class in the model HOT 1
- offline usage
- rgb.npy and flow.npy HOT 3
- training from scratch HOT 2
- which one is the checkpoint? HOT 5
- The problem of receptive field in I3D paper
- missing videos
- Does the video need to be cropped? HOT 11
- Calculation of TV L1 flow HOT 1
- dependencies issues HOT 1
- Struggling to learn using Opt. Flow HOT 2
- Incompatibility issues
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- Is there Model File(.pth or .pt) that pretrained with Imagenet+Kinetics?
- I found the pth file which pretrained on Kinetics400 HOT 1
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