Search Results for author: Li Nanbo

Found 4 papers, 1 papers with code

Align-Deform-Subtract: An Interventional Framework for Explaining Object Differences

no code implementations9 Mar 2022 Cian Eastwood, Li Nanbo, Christopher K. I. Williams

Given two object images, how can we explain their differences in terms of the underlying object properties?

Learning Object-Centric Representations of Multi-Object Scenes from Multiple Views

1 code implementation NeurIPS 2020 Li Nanbo, Cian Eastwood, Robert B. Fisher

In order to sidestep the main technical difficulty of the multi-object-multi-view scenario -- maintaining object correspondences across views -- MulMON iteratively updates the latent object representations for a scene over multiple views.

Scene Understanding

Object-Centric Representation Learning with Generative Spatial-Temporal Factorization

no code implementations NeurIPS 2021 Li Nanbo, Muhammad Ahmed Raza, Hu Wenbin, Zhaole Sun, Robert B. Fisher

We train DyMON on multi-view-dynamic-scene data and show that DyMON learns -- without supervision -- to factorize the entangled effects of observer motions and scene object dynamics from a sequence of observations, and constructs scene object spatial representations suitable for rendering at arbitrary times (querying across time) and from arbitrary viewpoints (querying across space).

Representation Learning

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