VideoCutLER

VideoCutLER is a simple unsupervised video instance segmentation method (UnVIS) that uses a cut-synthesis-and-learn pipeline to generate pseudo-masks for multiple objects in an image and then train an unsupervised video instance segmentation model using these mask trajectories.

Data and Resources

Cite this as

Xudong Wang, Ishan Misra, Ziyun Zeng, Rohit Girdhar, Trevor Darrell (2024). Dataset: VideoCutLER. https://doi.org/10.57702/36zuzsav

DOI retrieved: December 16, 2024

Additional Info

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Created December 16, 2024
Last update December 16, 2024
Author Xudong Wang
More Authors
Ishan Misra
Ziyun Zeng
Rohit Girdhar
Trevor Darrell
Homepage https://github.com/facebookresearch/CutLER