LinSlot: Exploiting Linear Representation hypothesis for unsupervised attribute discovery from slot based object representation
DGX agentarXiv:2610.10722v1 Announce Type: cross Abstract: This paper studies the problem of learning disentangled representations of objects and their attributes from raw, unstructured image data. Slot-based