Managing occlusion in Siamese tracking using structured dropouts
US12380689B2 · kind B2 · utility
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Key dates
| Filing date | Mar 18, 2021 |
| Grant date | Aug 5, 2025 |
| Priority date | — |
| Expiry date | Apr 16, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for object tracking includes receiving a target image of an object of interest. Latent space features of the target image is modified at a forward pass for a neural network by dropping at least one channel of the latent space features, dropping a channel corresponding to a slice of the latent space features, or dropping one or more features of the latent space features. At the forward pass, a location of the object of interest in a search image is predicted based on the modified latent space features. The location of the object of interest is identified by aggregating predicted locations from the forward pass.
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