We present ViLBERT (short for Vision-and-Language BERT), a model for learning task-
agnostic joint representations of image content and natural language. We extend the …

State-of-the-art navigation methods leverage a spatial memory to generalize to new
environments, but their occupancy maps are limited to capturing the geometric structures …

From a single image, humans are able to perceive the full 3D shape of an object by
exploiting learned shape priors from everyday life. Contemporary single-image 3D …

Several animal species (eg, bats, dolphins, and whales) and even visually impaired humans
have the remarkable ability to perform echolocation: a biological sonar used to perceive …

In this work, we address the problem of action recognition in a multi-view environment. Most
of the existing approaches utilize pose information for multi-view action recognition. We …

It is common to implicitly assume access to intelligently captured inputs (eg, photos from a
human photographer), yet autonomously capturing good observations is itself a major …

The growing amounts of online multimedia content challenge the current search,
recommendation and information retrieval systems. Information in the form of visual …

An undeniable part of a smart city is its use of smart agents. These agents can vary a lot in
sizes, shapes, and functionalities. Embodied artificial intelligence is the field of study that …

Estimating the relative rigid pose between two RGB-D scans of the same underlying
environment is a fundamental problem in computer vision, robotics, and computer graphics …

Visual recognition systems mounted on autonomous moving agents face the challenge of
unconstrained data, but simultaneously have the opportunity to improve their performance …