226 citations · 750 across the 46 of their papers we have counts for
5 papers · 1 filter
An Interpretable Model for Scene Graph Generation
Ji Zhang, Kevin Shih, Andrew Tao +2
We propose an efficient and interpretable scene graph generator. We consider three types of features: visual, spatial and semantic, and we use a late fusion strategy such that each…
Introduction to the 1st Place Winning Model of OpenImages Relationship Detection Challenge
Ji Zhang, Kevin Shih, Andrew Tao +2
This article describes the model we built that achieved 1st place in the OpenImage Visual Relationship Detection Challenge on Kaggle. Three key factors contribute the most to our s…
Disconnected Manifold Learning for Generative Adversarial Networks
Mahyar Khayatkhoei, Ahmed Elgammal, Maneesh Singh
Natural images may lie on a union of disjoint manifolds rather than one globally connected manifold, and this can cause several difficulties for the training of common Generative A…
Large-Scale Visual Relationship Understanding
Ji Zhang, Yannis Kalantidis, Marcus Rohrbach +3
Large scale visual understanding is challenging, as it requires a model to handle the widely-spread and imbalanced distribution of <subject, relation, object> triples. In real-worl…
The Shape of Art History in the Eyes of the Machine
Ahmed Elgammal, Marian Mazzone, Bingchen Liu +2
How does the machine classify styles in art? And how does it relate to art historians' methods for analyzing style? Several studies have shown the ability of the machine to learn a…