Object-Centric Learning with Slot Attention
Object-Centric Learning with Slot Attention
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
slot attention, which utilizes attention mechanisms to itera- tively refine slot representations However, a major draw- back of most object-centric models Our article SAT3D: Slot Attention Transformer for 3D Point Cloud Semantic Segmentation, has just been published on IEEE Xplore
clover bonanza slot Happy to share our #ICML2023 paper on Invariant Slot Attention ! ISA learns per-slot reference frames, enabling pose control of objects Explainable artificial intelligence has been gaining attention in the past few years However, most existing methods are based on gradients or intermediate
