New benchmark tests if AI can track objects after they vanish from view

Beyond3D challenges vision-language models to reason about relocated objects no longer visible in egocentric video.

Big Tech
Fangzhou Ma · Ivo Alexander Ban · Eren Homburg · Gabriele Goletto · Rémi Pautrat · Mahdi Rad · +2 more

ETH Zurich · Microsoft Spatial AI Lab · Bocconi University

Research Digest··2 min read
Ma et al.

The authors constructed Beyond3D from the HD-EPIC dataset, which provides 3D scene reconstructions and annotations of object movements during unscripted cooking and everyday activities.

Why this paper

From Microsoft Spatial AI Lab and 2 others

In one line

Vision-language models struggle to reason about objects moved out of sight, reaching only 42.2% on a new 9,000-question egocentric video benchmark.

What we could check

  • ·No code link found
  • ·No weights link found
  • ·No dataset link found
  • ·No compute details found
  • ·No stated limitations found
  • ✓Reports numbers on named benchmarks

Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.

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