MOSE-api
[ICCV 2023] MOSE: A New Dataset for Video Object Segmentation in Complex Scenes (by henghuiding)
tcow
Tracking through Containers and Occluders in the Wild (CVPR 2023) - Official Implementation (by basilevh)
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
MOSE-api
Posts with mentions or reviews of MOSE-api.
We have used some of these posts to build our list of alternatives
and similar projects.
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🔥 Meet MOSE: A New Dataset for Video Object Segmentation in Complex Scenes
🔗 Quick Read: https://www.marktechpost.com/2023/02/10/meet-mose-a-new-dataset-for-video-object-segmentation-in-complex-scenes/ 🔗 Paper: https://arxiv.org/pdf/2302.01872.pdf 🔗 Github: https://github.com/henghuiding/MOSE-api 🔗 Project: https://henghuiding.github.io/MOSE/
tcow
Posts with mentions or reviews of tcow.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Tracking through Containers and Occluders in the Wild- Meet TCOW: An AI Model that can Segment Objects in Videos with a Notion of Object Permanence
Github: https://github.com/basilevh/tcow
What are some alternatives?
When comparing MOSE-api and tcow you can also consider the following projects:
sa-uta11-results - 📈 [CHI 2023] Results of the statistical analysis applied to the UTA11 guide.
rtdl - Research on Tabular Deep Learning [Moved to: https://github.com/yandex-research/rtdl]