Comments (7)
The details are listed in the appendix.
The instructions here https://github.com/hkchengrex/Tracking-Anything-with-DEVA/blob/main/docs/EVALUATION.md#open-worldlarge-vocabularyunsupervised-video-object-segmentation and https://github.com/hkchengrex/Tracking-Anything-with-DEVA/blob/main/docs/EVALUATION.md#unsupervised-salient-video-object-segmentation might help.
You can also try the demo https://github.com/hkchengrex/Tracking-Anything-with-DEVA/blob/main/docs/DEMO.md.
Unfortunately, I do not have the domain knowledge to tell which approach is the "best".
from tracking-anything-with-deva.
My dataset is such that, in some videos it has single object and in some videos has more than one objects, in that case if I use your pretrained temporal model as temporal propagation and for image segmentation model follow the approach you did for DAVIS-2017(Multi object unsupervised video object segmentation), then can I compare the results with other models? I mean can I say this is DEVA's results on our dataset?
from tracking-anything-with-deva.
If a reasonable image detection model is used, I don't see why not.
from tracking-anything-with-deva.
Sorry for disturbing so much, my main question is that if I don't choose any other image detection model, I use the same image detection and temporal propagation models which you have used for DAVIS 2017, then can I say this is the result of DEVA on my dataset? or I have to find a specific image detection model for my data and use your temporal propagation model for comparison.
from tracking-anything-with-deva.
No matter which image detector you use, as long as you specify it, I don't see why you don't state it that way. I cannot comment on whether it poses a fair comparison or presents meaningful results -- I think you would be a much better judge of that.
from tracking-anything-with-deva.
Ok. Thank you so much for your patience. I appreciate it.
However, I want to have your advise in more thing, as I said before my data set is such that in some videos it has single object and in some videos has more than one objects, in this case using the approash you used for DAVIS 2016 is advised or the one which you used for DAVIS 2017?
from tracking-anything-with-deva.
The DAVIS 16 approach only works for a single (salient) object and would not work for videos with multiple objects.
from tracking-anything-with-deva.
Related Issues (20)
- Installation issue HOT 6
- Have you made all the code public? HOT 1
- Error while inference HOT 14
- Unexpected segmentation output HOT 7
- Is ovis used for training networks? Do you have a download link๏ผ HOT 5
- Train error HOT 14
- Can your method be applied to other video segmentation tasks? HOT 1
- About training details HOT 1
- Why is the training speed of DEVA much slower than XMem? HOT 3
- Is it normal for DEVA's training speed to be much slower than XMem? HOT 5
- Not working if there is large variation between consecutive frames?? HOT 5
- Deva out of memory HOT 3
- Deva run out of memory with "Including non-PyTorch memory, this process has 17179869184.00 GiB memory in use." HOT 1
- Pre-trained model HOT 1
- None in category_ids HOT 2
- Is there a way to use DEVA with Cutie? HOT 3
- How to inference a video directly HOT 2
- Licence HOT 1
- Deva on CPU HOT 1
- Crop / segment the objects HOT 1
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from tracking-anything-with-deva.