HoloAssist: an Egocentric Human Interaction Dataset for Interactive AI Assistants in the Real World
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Cited by 22 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
Building an interactive AI assistant that can perceive, reason, and collaborate with humans in the real world has been a long-standing pursuit in the AI community. This work is part of a broader research effort to develop intelligent agents that can interactively guide humans through performing tasks in the physical world. As a first step in this direction, we introduce HoloAssist, a large-scale egocentric human interaction dataset, where two people collaboratively complete physical manipulation tasks. The task performer executes the task while wearing a mixed-reality headset that captures seven synchronized data streams. The task instructor watches the performer's egocentric video in real time and guides them verbally. By augmenting the data with action and conversational annotations and observing the rich behaviors of various participants, we present key insights into how human assistants correct mistakes, intervene in the task completion procedure, and ground their instructions to the environment. HoloAssist spans 166 hours of data captured by 350 unique instructor-performer pairs. Furthermore, we construct and present benchmarks on mistake detection, intervention type prediction, and hand forecasting, along with detailed analysis. We expect HoloAssist will provide an important resource for building AI assistants that can fluidly collaborate with humans in the real world. Data can be downloaded at https://holoassist.github.io/.
Key facts. Cited by 166 papers in the map (data through 14 Oct 2026). Builds on 31 of its 44 references that are in the map. First posted on arXiv 29 Sep 2023.
Builds on
31 of 44 references.
References · 31
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- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
- 2014Sequence to Sequence Learning with Neural Networkscited by 2,986
- 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,348
- 2021Is Space-Time Attention All You Need for Video Understanding?cited by 1,620
- 2021Ego4D: Around the World in 3,000 Hours of Egocentric Videocited by 1,556
- 2019Habitat: A Platform for Embodied AI Researchcited by 1,191
- 2017AI2-THOR: An Interactive 3D Environment for Visual AIcited by 869
- 2019ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Taskscited by 783
- 2022Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulationcited by 551
- 2020Rescaling Egocentric Visioncited by 540
19 more
- 2021Habitat 2.0: Training Home Assistants to Rearrange their Habitatcited by 511
- 2018VirtualHome: Simulating Household Activities via Programscited by 415
- 2022HOI4D: A 4D Egocentric Dataset for Category-Level Human-Object Interactioncited by 327
- 2022Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural Activitiescited by 287
- 2021H2O: Two Hands Manipulating Objects for First Person Interaction Recognitioncited by 254
- 2019Vision-and-Dialog Navigationcited by 250
- 2021TEACh: Task-driven Embodied Agents that Chatcited by 197
- 2021BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environmentscited by 165
- 2021EgoBody: Human Body Shape and Motion of Interacting People from Head-Mounted Devicescited by 139
- 2015Unsupervised Learning from Narrated Instruction Videoscited by 116
- 2022Joint Hand Motion and Interaction Hotspots Prediction from Egocentric Videoscited by 111
- 2022GIMO: Gaze-Informed Human Motion Prediction in Contextcited by 81
- 2020The MECCANO Dataset: Understanding Human-Object Interactions from Egocentric Videos in an Industrial-like Domaincited by 79
- 2022TL;DW? Summarizing Instructional Videos with Task Relevance & Cross-Modal Saliencycited by 35
- 2022AssistQ: Affordance-centric Question-driven Task Completion for Egocentric Assistantcited by 32
- 2022Towards Open Set Video Anomaly Detectioncited by 26
- 2022Interactive Grounded Language Understanding in a Collaborative Environment: IGLU 2021cited by 23
- 2022IGLU Gridworld: Simple and Fast Environment for Embodied Dialog Agentscited by 9
- 2022Human in the loop approaches in multi-modal conversational task guidance system developmentcited by 2
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Citing papers per year: 2023: 2; 2024: 26; 2025: 62; 2026: 76.
166 papers.
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