Comments (3)
Hello,
We use the official code released in python and matlab here.
In the evaluation of DAVIS 2016 the three metrics that you mention are used for evaluation. In DAVIS 2017, region similarity and contour accuracy are used as there are more occlusions and temporal stability is not reliable in such scenario.
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Thank you very much! I have some doubts about the train_online.py file.The online training here uses a training set to train the network and then test the network using the test set. Not what you said by using the first frame of the test sequence to learn the appearance of the object. So I am a bit confused. thank you !
from osvos-pytorch.
Hi, it is the definition of supervised video object segmentation to be given the label of the first frame and train on that. We separate our training in two steps: 1. training on generic foreground labels and 2. during test time, train on the mask of the given object.
from osvos-pytorch.
Related Issues (20)
- Code HOT 1
- class_balanced_cross_entropy_loss HOT 1
- Confused by " inputs.requires_grad_()" HOT 3
- online training HOT 1
- Why total iterations are different to them in the paper? HOT 1
- official measure code HOT 7
- How to add Mask Input? HOT 1
- Can you deliver a pretrain .pth model file of the final model HOT 1
- loss islarge HOT 3
- i can't find where you use finetuning on first frame in your code-pytorch HOT 5
- can you help me, how to use this code on Davis 2017 HOT 2
- train_online RuntimeError HOT 1
- The code of contour snap HOT 1
- Optimizer learning rates HOT 1
- Question about evaluation result HOT 1
- an error occurred when running train_parent.py HOT 6
- How to Evaluate the model? HOT 1
- Can it be used in images? HOT 1
- Emergency!
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