Unlocking Slot Attention by Changing Optimal Transport Costs

Second, instead of applying recurrent function to update slots over multiple iterations in original slot attention , our tailor-modified PRSlot module

Unlocking Slot Attention by Changing Optimal Transport Costs We empirically demonstrate that Slot Attention can extract object-centric representations that enable generalization to unseen compositions when trained on

Second, instead of applying recurrent function to update slots over multiple iterations in original slot attention , our tailor-modified PRSlot module

slotoostendegoesnetherlands slot attention to a multi-query approach, allowing the model to learn multiple sets of slots, producing more stable masks During training

Abstract Slot attention has shown remarkable object- centric representation learning performance in computer vision tasks without requiring any super-

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Based on PRSlot modules, we present a novel Pyramid Region-based Slot Attention Network termed PRSA-Net to learn a unified visual representation with rich