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Found 9 papers, 5 papers with code
Using Motion Forecasting for Behavior-Based Virtual Reality (VR) Authentication
In this work, we present the first approach that predicts future user behavior using Transformer-based forecasting and using the forecasted trajectory to perform user authentication.
Evaluating Deep Networks for Detecting User Familiarity with VR from Hand Interactions
As VR devices become more prevalent in the consumer space, VR applications are likely to be increasingly used by users unfamiliar with VR.
HOH: Markerless Multimodal Human-Object-Human Handover Dataset with Large Object Count
We present the HOH (Human-Object-Human) Handover Dataset, a large object count dataset with 136 objects, to accelerate data-driven research on handover studies, human-robot handover implementation, and artificial intelligence (AI) on handover parameter estimation from 2D and 3D data of person interactions.
Pix2Repair: Implicit Shape Restoration from Images
We also introduce Fantastic Breaks Imaged, the first large-scale dataset of 11, 653 real-world images of fractured objects for training and evaluating image-based shape repair approaches.
Fantastic Breaks: A Dataset of Paired 3D Scans of Real-World Broken Objects and Their Complete Counterparts
Automated shape repair approaches currently lack access to datasets that describe real-world damaged geometry.
Simultaneous prediction of hand gestures, handedness, and hand keypoints using thermal images
In this work, we propose a technique for simultaneous hand gesture classification, handedness detection, and hand keypoints localization using thermal data captured by an infrared camera.
DeepJoin: Learning a Joint Occupancy, Signed Distance, and Normal Field Function for Shape Repair
We generate a high-resolution restoration shape by inferring a corresponding complete shape and a break surface from an input fractured shape.
DeepMend: Learning Occupancy Functions to Represent Shape for Repair
We represent the occupancy of a fractured shape as the conjunction of the occupancy of an underlying complete shape and the fracture surface, which we model as functions of latent codes using neural networks.
Panoptic Studio: A Massively Multiview System for Social Interaction Capture
The core challenges in capturing social interactions are: (1) occlusion is functional and frequent; (2) subtle motion needs to be measured over a space large enough to host a social group; (3) human appearance and configuration variation is immense; and (4) attaching markers to the body may prime the nature of interactions.
