Object-Centric Learning with Slot Attention

slot attention
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The Slot Attention architecture works by first taking in the output of a convolutional neural network, which is a representation of the input image or dataset

In this paper, we present the Slot Attention module, an architectural component that interfaces with perceptual representations such as the

slot hileleri A widely adopted method within OCL is slot attention, which utilizes attention mechanisms to iteratively refine slot representations However, a major

slot machine picture to model slot type attention and slot value attention simultaneously and capture their Hybrid-Attention based on Slot-Attention and Link-Attention