October 9, 2025Open Access

Do You Know Where Your Camera Is? View-Invariant Policy Learning with Camera Conditioning

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Conditioning on camera extrinsics significantly enhances policy generalization across viewpoints.
Experiments in six manipulation tasks reveal policies without extrinsics struggle under scene variability.
Using Plucker embeddings of rays facilitates robust control without depth data, improving performance.
The study's findings indicate that camera conditioning is vital for effective imitation learning models.

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Implication

This analysis demonstrates improved policy robustness through camera conditioning in imitation learning, suggesting more effective viewpoint generalization.

Cite This Study

Jiang et al. (2025) studied this question.

synapsesocial.com/papers/68e7d631bd66d359be6266db https://doi.org/10.48550/arxiv.2510.02268

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Implication

This analysis demonstrates improved policy robustness through camera conditioning in imitation learning, suggesting more effective viewpoint generalization.

Do You Know Where Your Camera Is? View-Invariant Policy Learning with Camera Conditioning

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Discussion

Implication

Cite This Study

Do You Know Where Your Camera Is? View-Invariant Policy Learning with Camera Conditioning

Key Points

Discussion

Implication

Cite This Study

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