7 citations · 7 across the 4 of their papers we have counts for
6 papers · 1 filter
EscherNet 101
Christopher Funk, Yanxi Liu
A deep learning model, EscherNet 101, is constructed to categorize images of 2D periodic patterns into their respective 17 wallpaper groups. Beyond evaluating EscherNet 101 perform…
Novel 3D Scene Understanding Applications From Recurrence in a Single Image
Shimian Zhang, Skanda Bharadwaj, Keaton Kraiger +4
We demonstrate the utility of recurring pattern discovery from a single image for spatial understanding of a 3D scene in terms of (1) vanishing point detection, (2) hypothesizing 3…
Image-based Stability Quantification
Jesse Scott, John Challis, Robert T. Collins +1
Quantitative evaluation of human stability using foot pressure/force measurement hardware and motion capture (mocap) technology is expensive, time consuming, and restricted to the…
From Kinematics To Dynamics: Estimating Center of Pressure and Base of Support from Video Frames of Human Motion
Jesse Scott, Christopher Funk, Bharadwaj Ravichandran +3
To gain an understanding of the relation between a given human pose image and the corresponding physical foot pressure of the human subject, we propose and validate two end-to-end…
Learning Dynamics from Kinematics: Estimating 2D Foot Pressure Maps from Video Frames
Christopher Funk, Savinay Nagendra, Jesse Scott +4
Pose stability analysis is the key to understanding locomotion and control of body equilibrium, with applications in numerous fields such as kinesiology, medicine, and robotics. In…
Beyond Planar Symmetry: Modeling human perception of reflection and rotation symmetries in the wild
Christopher Funk, Yanxi Liu
Humans take advantage of real world symmetries for various tasks, yet capturing their superb symmetry perception mechanism with a computational model remains elusive. Motivated by…