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New ACE-Data-0 dataset tackles embodied AI data bottleneck

By PulseAugur Editorial · [2 sources] ·

Researchers have developed the Ambient Capture Engine (ACE), a system designed to address the data bottleneck in embodied intelligence. ACE transforms home environments into synchronized recording studios, capturing a comprehensive stream of data including first-person perception, whole-body motion, object interactions, audio, and tactile signals. This system has been used to create ACE-Data-0, a dataset featuring 150 hours of human demonstrations across various tasks and environments, intended to advance imitation learning and embodied AI systems. AI

IMPACT Provides a comprehensive dataset to accelerate research in imitation learning and embodied AI systems.

RANK_REASON The cluster describes a new dataset and associated engine for embodied AI research, published on arXiv and Hugging Face.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New ACE-Data-0 dataset tackles embodied AI data bottleneck

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The cluster describes a new dataset and associated engine for embodied AI research, published on arXiv and Hugging Face.
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COVERAGE [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    ACE-Data-0: Human-Centric Ambient Capture as Embodied Data Engine

    Embodied intelligence faces a fundamental data bottleneck. Models must capture how first-person perception, whole-body motion, dexterous manipulation, object state, sound, and touch evolve together as humans pursue goals over time. Existing datasets fragment this experience acros…

  2. arXiv cs.CV TIER_1 English(EN) · Yukang Cao, Haozhe Xie, Beichen Wen, Runmao Yao, Yinghao Liu, Yue Huang, Zhichao Liao, Yunxiang Wang, Haiheng Liu, Xingshun Tian, Dawei Su, Long Zhuo, Dacheng Tao, Xiaogang Wang, Liang Pan, Ziwei Liu ·

    ACE-Data-0: Human-Centric Ambient Capture as Embodied Data Engine

    arXiv:2607.28625v1 Announce Type: new Abstract: Embodied intelligence faces a fundamental data bottleneck. Models must capture how first-person perception, whole-body motion, dexterous manipulation, object state, sound, and touch evolve together as humans pursue goals over time. …

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