Our overarching research goal is to learn compositional models of grounded attributes towards describing an object in a scene, rather than just identifying it.
we do not only learn to recognize instances of objects, but also learn attributes constrained to feature spaces that will be compatible with contextual modifiers such as dark/light in terms of color, or small/large in terms of size and object classification.