Never Look Back: Understanding Persistence in 3D Object Memory from Egocentric Videos

Key points

• As we move through the world and carry out everyday tasks, we encounter objects that may become relevant only later.1
• Here, we study how an embodied assistant can build a similar memory from egocentric videos, by observing a person's day-to-day activities.1
• It associates observations across the recording and retains objects after they leave the view, including those the person never touches.1
• Our analyses identify complementary roles for temporal persistence, contextual descriptions, and retrieval.1

Sources (1)

• [1]Never Look Back: Understanding Persistence in 3D Object Memory from Egocentric Videos
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 05:59 PM

  We present Ledger, a persistent 3D object memory that combines object locations, their histories, and contextual descriptions.

  As we move through the world and carry out everyday tasks, we encounter objects that may become relevant only later.

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