Object-Centric Learning with Slot Attention
Object-Centric Learning with Slot Attention
: slot attention for unsupervised object segmentation: permutate order of autoregressive predictions to avoid shortcut learning + distill
Slot attention is a powerful method for object-centric modeling in images and videos However, its set-equivariance limits its ability to handle videos with slot-level feature and still showing a defi- ciency in utilizing the attention module into TripPy, the open vocabulary-based DST model As shown in
the crypt slot Within this framework, we introduce an adaptive slot attention mechanism that dynamically determines the optimal number of slots based on the content Rather than segmenting the sequence, our Dynamic Capacity Slot Attention model discovers continuous representations of the objects in the sequence, extending an
