UNINEXT
py-motmetrics
UNINEXT | py-motmetrics | |
---|---|---|
2 | 1 | |
1,443 | 1,324 | |
- | - | |
5.5 | 4.4 | |
10 months ago | 14 days ago | |
Python | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
UNINEXT
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[R] Universal Instance Perception as Object Discovery and Retrieval (Video Demo)
Hi, we have uploaded the complete paper (https://github.com/MasterBin-IIAU/UNINEXT/blob/master/assets/UNINEXT_Paper.pdf) to our repo. You can find more details in the paper :) About the first question, the input videos are NOT segmented aforehand and all target masks are predicted by our UNINEXT model. For SOT and VOS, we use target annotations (box or mask) from the first frame as the prompts. This helps UNINEXT to segment corresponding targets in the following frames.
py-motmetrics
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HOW to find MOTA and MOTP for MOT evaluation metrics?
I think this repo is a great starting point for your question: https://github.com/cheind/py-motmetrics
What are some alternatives?
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