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An Outlook into the Future of Egocentric Vision

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arxiv 2308.07123 v2 pith:B6QMYXHR submitted 2023-08-14 cs.CV

classification cs.CV
keywords futureegocentricvisioncurrentresearchsurveythenalways-on
verification ladder T0 review T1 audit T2 compute T3 formal
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What will the future be? We wonder! In this survey, we explore the gap between current research in egocentric vision and the ever-anticipated future, where wearable computing, with outward facing cameras and digital overlays, is expected to be integrated in our every day lives. To understand this gap, the article starts by envisaging the future through character-based stories, showcasing through examples the limitations of current technology. We then provide a mapping between this future and previously defined research tasks. For each task, we survey its seminal works, current state-of-the-art methodologies and available datasets, then reflect on shortcomings that limit its applicability to future research. Note that this survey focuses on software models for egocentric vision, independent of any specific hardware. The paper concludes with recommendations for areas of immediate explorations so as to unlock our path to the future always-on, personalised and life-enhancing egocentric vision.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Vinci2: Providing Proactive Assistance in Continuous Egocentric Videos

    cs.CV 2026-07 conditional novelty 6.5 of 10

    EgoMemo uses multi-scale temporal summaries, a knowledge graph, and visual archives to decide whether and when to intervene proactively on continuous egocentric video, setting baselines on the new EgoServe benchmark o...

  2. ObjectStream: Latent Objects as Memory Anchors for Streaming Video Understanding

    cs.CV 2026-07 conditional novelty 6.0 of 10

    Training-free latent-object memory anchors let frozen Video-LLMs retain object histories under a tight token budget and improve streaming and long-video QA.

  3. Vinci: A Real-time Embodied Smart Assistant based on Egocentric Vision-Language Model

    cs.CV 2024-12 conditional novelty 5.0 of 10

    A real-time egocentric assistant combines a vision-language model, memory, video retrieval, and video generation to answer questions and show how-to guidance from live wearable camera streams.

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