Simpler unsupervised object segmentation in videos using spectral clustering with SSL-VOS

Simpler unsupervised object segmentation in videos using spectral clustering with SSL-VOS

A Simple and Powerful Global Optimization for Unsupervised Video Object Segmentation
arXiv paper abstract https://arxiv.org/abs/2209.09341v1
arXiv PDF paper https://arxiv.org/pdf/2209.09341v1.pdf

… propose a simple, yet powerful approach for unsupervised object segmentation in videos.

… introduce an objective function whose minimum represents the mask of the main salient object over the input sequence.

It only relies on independent image features and optical flows, which can be obtained using off-the-shelf self-supervised methods.

It scales with the length of the sequence with no need for superpixels or sparsification, and it generalizes to different datasets without any specific training.

This objective function can actually be derived from a form of spectral clustering applied to the entire video.

… method achieves on-par performance with the state of the art on standard benchmarks (DAVIS2016, SegTrack-v2, FBMS59), while being conceptually and practically much simpler …

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I apply innovative technologies like machine learning, computer vision, and physics to further an organization's goals. Am recognized innovator with 66 patents.