Object-Centric Learning with Slot Attention

Visual scenes are often comprised of sets of independent objects. Yet, current vision models make no assumptions about the nature of the pictures they look at.

Yannic Kilcher explore a paper on object-centric learning.

By imposing an objectness prior, this paper a module that is able to recognize permutation-invariant sets of objects from pixels in both supervised and unsupervised settings. It does so by introducing a slot attention module that combines an attention mechanism with dynamic routing.

Content index:

  • 0:00 – Intro & Overview
  • 1:40 – Problem Formulation
  • 4:30 – Slot Attention Architecture
  • 13:30 – Slot Attention Algorithm
  • 21:30 – Iterative Routing Visualization
  • 29:15 – Experiments
  • 36:20 – Inference Time Flexibility
  • 38:35 – Broader Impact Statement
  • 42:05 – Conclusion & Comments

Frank

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