Transformer is a promising neural network learner, and has achieved great success in
various machine learning tasks. Thanks to the recent prevalence of multimodal applications …

A major goal of artificial intelligence (AI) is to create an agent capable of acquiring a general
understanding of the world. Such an agent would require the ability to continually …

Existing person re-identification methods often suffer significant performance degradation on
unseen domains, which fuels interest in domain generalizable person re-identification (DG …

In recent years, remarkable achievements have been made in artificial intelligence tasks
and applications based on deep neural networks (DNNs), especially in the fields of vision …

We propose CX-ToM, short for counterfactual explanations with theory-of-mind, a new
explainable AI (XAI) framework for explaining decisions made by a deep convolutional …

Deep learning models, though having achieved great success in many different fields over
the past years, are usually data-hungry, fail to perform well on unseen samples, and lack …

We present a method for inferring diverse 3D models of human-object interactions from
images. Reasoning about how humans interact with objects in complex scenes from a single …

Humans predominantly use verbal utterances and nonverbal gestures (eg, eye gaze and
pointing gestures) in their natural interactions. For instance, pointing gestures and verbal …

Compositional generalization has received much attention in vision-and-language and
visual reasoning recently. Substitutivity, the capability to generalize to novel compositions …

Humans naturally use referring expressions with verbal utterances and nonverbal gestures
to refer to objects and events. As these referring expressions can be interpreted differently …