A single diffusion policy trained with DAgger, without a waypoint predictor, reports better performance than two-stage waypoint-based models on VLN-CE benchmarks.
Retrospectives on the Embodied AI Workshop
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abstract
We present a retrospective on the state of Embodied AI research. Our analysis focuses on 13 challenges presented at the Embodied AI Workshop at CVPR. These challenges are grouped into three themes: (1) visual navigation, (2) rearrangement, and (3) embodied vision-and-language. We discuss the dominant datasets within each theme, evaluation metrics for the challenges, and the performance of state-of-the-art models. We highlight commonalities between top approaches to the challenges and identify potential future directions for Embodied AI research.
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cs.RO 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
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DAgger Diffusion Navigation: DAgger Boosted Diffusion Policy for Vision-Language Navigation
A single diffusion policy trained with DAgger, without a waypoint predictor, reports better performance than two-stage waypoint-based models on VLN-CE benchmarks.