Publications

January 1, 2020

Ethics in Design and Communication 2020

Virtual Reality (VR) designers accept the ethical responsibilities of removing a user’s entire world and superseding it with a fabricated reality. These unique immersive design challenges are intensified when virtual experiences become public and socially-driven. As female VR designers in 2018, we see an opportunity to fold the language of consent into the design practice of virtual reality—as a means to design safe, accessible, virtual spaces.

Publication will be made available in 2020.

Areas: AR/VR Human Computer Interaction & UX

February 16, 2019

IEEE International Symposium on High-Performance Computer Architecture (HPCA)

This paper takes a data-driven approach to present the opportunities and design challenges faced by Facebook in order to enable machine learning inference locally on smartphones and other edge platforms.

Areas: AR/VR Machine Learning Systems & Networking

December 17, 2018

Advanced Functional Materials 2018

The design and fabrication of a rolled dielectric elastomer actuator is described and the parametric dependence of the displacement and blocked force on the actuator geometry, elastomer layer thickness, voltage, and number of turns is analyzed.

Areas: AR/VR

December 4, 2018

ACM SIGGRAPH Asia 2018

In this paper, we introduce DeepFocus, a generic, end-to-end convolutional neural network designed to efficiently solve the full range of computational tasks for accommodation-supporting HMDs. This network is demonstrated to accurately synthesize defocus blur, focal stacks, multilayer decompositions, and multiview imagery using only commonly available RGB-D images, enabling real-time, near-correct depictions of retinal blur with a broad set of accommodation-supporting HMDs.

Areas: AR/VR Machine Learning

October 25, 2018

Scientific Reports 2018

It has been suggested that the integration of multiple body-related sources of information within the peri-personal space (PPS) scaffolds body ownership. However, a normative computational framework detailing the functional role of PPS is still missing. Here we cast PPS as a visuo-proprioceptive Bayesian inference problem whereby objects we see in our environment are more likely to engender sensations as they come near to the body. We propose that PPS is the refection of such an increased a priori probability of visuo-proprioceptive coupling that surrounds the body.

Areas: AR/VR

October 12, 2018

International Symposium on Wearable Computers 2018

We propose using a multi-sensory haptic device called MISSIVE, which can be worn on the upper arm and is capable of producing brief cues, sufficient in quantity to encode the full English phoneme set.

Areas: AR/VR Human Computer Interaction & UX

October 1, 2018

Human Factors and Ergonomics Society

The minimum contrast needed for optimal text readability with additive displays (e.g. AR devices) will depend on the spatial structure of the background and text. Natural scenes and text follow similar spectral patterns. Therefore, natural scenes can mask low contrast text – making it difficult to read. In a set of experiments, we determine the minimum viable contrast for readability on an additive display.

Areas: AR/VR

September 8, 2018

European Conference on Computer Vision (ECCV)

We present a novel method to generate accurate and realistic clothing deformation from real data capture. Previous methods for realistic cloth modeling mainly rely on intensive computation of physics-based simulation (with numerous heuristic parameters), while models reconstructed from visual observations typically suffer from lack of geometric details.

Areas: AR/VR Computer Vision Facebook AI Research Machine Learning

September 7, 2018

European Conference on Computer Vision (ECCV)

We introduce a data-driven approach for unsupervised video retargeting that translates content from one domain to another while preserving the style native to a domain, i.e., if contents of John Oliver’s speech were to be transferred to Stephen Colbert, then the generated content/speech should be in Stephen Colbert’s style.

Areas: AR/VR Computer Vision Facebook AI Research Machine Learning

September 3, 2018

British Machine Vision Convention (BMVC)

Deep learning for predicting or generating 3D human pose sequences is an active research area. Previous work regresses either joint rotations or joint positions. The former strategy is prone to error accumulation along the kinematic chain, as well as discontinuities when using Euler angle or exponential map parameterizations. The latter requires re-projection onto skeleton constraints to avoid bone stretching and invalid configurations. This work addresses both limitations.

Areas: AR/VR Computer Vision Facebook AI Research