Pyramid Region-based Slot Attention Network for Temporal Action

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

Pyramid Region-based Slot Attention Network for Temporal Action : slot attention for unsupervised object segmentation: permutate order of autoregressive predictions to avoid shortcut learning + distill

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

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slot attention, which utilizes attention mechanisms to itera- tively refine slot representations However, a major draw- back of most object-centric models

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Slot Attention is an architectural component that interfaces with perceptual representations such as the output of a convolutional neural network and