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Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
This paper takes an axiomatic perspective to derive the desired properties and invariances of a such network to certain input permutations, presenting a structural characterization that is provably both necessary and sufficient. Expand
Differentiable Scene Graphs
Differentiable Scene Graphs (DSGs) are proposed, an image representation that is amenable to differentiable end-to-end optimization, and requires supervision only from the downstream tasks. Expand
Learning Latent Scene-Graph Representations for Referring Relationships
This work describes a family of models that uses scene-graph like representations, and uses them in downstream tasks, and shows how these representations can be trained from partial supervision. Expand