271 citations · 1.2k across the 14 of their papers we have counts for
5 papers · 1 filter
Linking vision and motion for self-supervised object-centric perception
Kaylene C. Stocking, Zak Murez, Vijay Badrinarayanan +4
Object-centric representations enable autonomous driving algorithms to reason about interactions between many independent agents and scene features. Traditionally these representat…
SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition
Rishabh Kabra, Daniel Zoran, Goker Erdogan +5
To help agents reason about scenes in terms of their building blocks, we wish to extract the compositional structure of any given scene (in particular, the configuration and charac…
Unsupervised Object-Based Transition Models for 3D Partially Observable Environments
Antonia Creswell, Rishabh Kabra, Chris Burgess +1
We present a slot-wise, object-based transition model that decomposes a scene into objects, aligns them (with respect to a slot-wise object memory) to maintain a consistent order a…
AlignNet: Unsupervised Entity Alignment
Antonia Creswell, Kyriacos Nikiforou, Oriol Vinyals +8
Recently developed deep learning models are able to learn to segment scenes into component objects without supervision. This opens many new and exciting avenues of research, allowi…
MONet: Unsupervised Scene Decomposition and Representation
Christopher P. Burgess, Loic Matthey, Nicholas Watters +4
The ability to decompose scenes in terms of abstract building blocks is crucial for general intelligence. Where those basic building blocks share meaningful properties, interaction…