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Found 3 papers, 1 papers with code
Subspace Identification for Multi-Source Domain Adaptation
To mitigate the need for these strict assumptions, we propose a subspace identification theory that guarantees the disentanglement of domain-invariant and domain-specific variables under less restrictive constraints regarding domain numbers and transformation properties, thereby facilitating domain adaptation by minimizing the impact of domain shifts on invariant variables.
Active Visual Localization for Multi-Agent Collaboration: A Data-Driven Approach
However, localizing e. g. a ground robot in the map of a drone or head-mounted MR headset presents unique challenges due to viewpoint changes.
See Yourself in Others: Attending Multiple Tasks for Own Failure Detection
The proposed framework infers task failures by evaluating the individual prediction, across multiple visual perception tasks for different regions in an image.
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