Here we explore whether a sparse representation of human touch is sufficient to convey social touch signals. To test this we collected a dataset of social touch interactions using a soft wearable pressure sensor array, developed an algorithm to map recorded data to an array of actuators, then applied our algorithm to create signals that drive an array of normal indentation actuators placed on the arm.
We then train a new two-layer codec avatar with separate modeling of the upper clothing and the inner body layer. To learn the interaction between the body dynamics and clothing states, we use a temporal convolution network to predict the clothing latent code based on a sequence of input skeletal poses. We show photorealistic animation output for three different actors, and demonstrate the advantage of our clothed-body avatars over the single-layer avatars used in previous work.
To the best of our knowledge, F-CAD is the first automation tool that supports the whole design flow of hardware acceleration of codec avatar decoders, allowing joint optimization on decoder designs in popular machine learning frameworks and corresponding customized accelerator design with cycle-accurate evaluation.
We propose a method to estimate the bidirectional reflectance distribution function (BRDF) and shading of complete scenes under static illumination given the 3D scene geometry and a corresponding high dynamic range (HDR) video.
We propose to combine low-rank tensor decomposition with sparse pruning in order to take advantage of both coarse and fine structure for compression. We compress weights in SOTA architectures (MobileNetv3, EfficientNet, Vision Transformer) and compare this approach to sparse pruning and tensor decomposition alone.
In this work, a series of halogenated polymer thin films with high refractive indexes (n =1.7 - 2.0) and outstanding optical transparency in the visible and infrared range, were prepared via a unique vapor phase process – initiated chemical vapor deposition (iCVD).
In this paper, we focus on this problem and introduce a system composed of: 1) a haptic simulator leveraging high spatial resolution vision-based tactile sensors for active touching of 3D objects; 2) a mesh-based 3D shape reconstruction model that relies on tactile or visuotactile signals; and 3) a set of data-driven solutions with either tactile or visuotactile priors to guide the shape exploration.
In this paper, we present HWTool, a novel system for automatically mapping image processing and computer vision algorithms to hardware. Our system maps between two domains: HWImg, an extensible C++ image processing library containing common image processing and parallel computing operators, and Rigel2, a library of optimized hardware implementations of HWImg’s operators and backend Verilog compiler.
This paper describes a 210 participant study focused on behavioral measures that compares multiparty interaction in videoconference and embodied VR across a range of task types: a factual intellective task, a subjective judgment task and two negotiation tasks, one with visual grounding.