Comments (4)
Thanks for your attention. The training dataset will be released soon.
from lasted.
Thanks for your asking. It is very strange that loss cannot decrease in both labeling (e.g., r1 or r3). Could you provide more detailed information? Also, try using pre-trained weights (e.g., ImageNet), which will accelerate convergence.
from lasted.
I've tried similar training data with r3, but if we can reproduce your results so if its possible to release the training data?
That'd be very helpful
from lasted.
The training dataset can be downloaded from the following link. Due to Google Drive's capacity limitations, we are currently only able to share it via Baidu Pan: https://pan.baidu.com/s/1ZgSiNX_Dd7cZcwiHv1ujVg?pwd=h4p7
from lasted.
Related Issues (15)
- Train data and Openset issues HOT 3
- Issue with Openset testset HOT 5
- Request for an Alternative Download Method for the Training Dataset HOT 6
- Question about dataset used in the paper HOT 2
- Question about training time HOT 2
- Is there anyway to download the pretrained weights? HOT 1
- Training problem HOT 2
- Please provide unzip code HOT 4
- Questions HOT 1
- I try to train the model using code and the code has some errors HOT 1
- Some question for rerun the code HOT 8
- Some questions about the trainning HOT 2
- Do you have a paper/technical report to refer to more implementation details? HOT 1
- Model just predicts most images as real (painting or photo)
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from lasted.