arXiv Artificial Intelligence

What Moves? Localized Motion Representations for Compositional Scene Control

What Moves? Localized Motion Representations for Compositional Scene Control

Quick summary

arXiv:2609.04383v1 Announce Type: cross Abstract: Real-world dynamics are inherently compositional: multiple entities move simultaneously within a shared scene, each exhibiting distinct motion patterns. Yet most existing video representations encode motion globally, without explicitly capturing localized motion for individual entities. Crucially, motion is defined relative to a global reference frame, including camera motion and scene layout. However, localized embeddings are often computed from cropped images or obtained by masking features after encoding, discarding the context needed to int

Key takeaways

  • arXiv:2609.04383v1 Announce Type: cross Abstract: Real-world dynamics are inherently compositional: multiple entities move simultaneously within a shared scene, each exhibiting distinct motion patterns.
  • Yet most existing video representations encode motion globally, without explicitly capturing localized motion for individual entities.
  • Crucially, motion is defined relative to a global reference frame, including camera motion and scene layout.

Why it matters

“What Moves? Localized Motion Representations for Compositional Scene Control” illustrates how changes in the AI ecosystem can affect products, workflows and user expectations together. Its lasting significance depends on measurable adoption, cost and safety outcomes.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗