Disney Research Pittsburgh

In this paper, we tackle the largely overlooked problem of scheduling a multiplayer interactive narrative and propose the Live Interactive Narrative Scheduling Problem (LINSP), which handles reasoning under temporal uncertainty, resource scheduling, and non-linear plot choices.

We develop several interactive experiences where users can retrieve complex information such as the function of buttons on a device, directions embedded into a LCD screen, and simplified device pairing.

We introduce a spatial pyramid-like structure to the image and learn CNNs for image sub-regions at different scales.

We designed an augmented reality interface for dialog that enables the control of multimodal behaviors in telepresence robot applications.

This paper introduces an embodied agent that self-authors its own dialog for social chat.

To our best knowledge, this is the first large-scale study for automatic evaluation of narrative quality.

We study a mini-batch diversification scheme for stochastic gradient descent (SGD).

We present a probabilistic language model for time-stamped text data which tracks the semantic evolution of individual words over time.

We propose a joint approach that simultaneously learns a latent coordination model along with the individual policies.

In this work, we leverage advances in semiconductor optics, RF antenna design and system integration to create a hybrid RFID reader and smart LED lamp, in the form factor of a standard light bulb.