15 citations · 32 across the 10 of their papers we have counts for
13 papers
Grasp'D: Differentiable Contact-rich Grasp Synthesis for Multi-fingered Hands
Dylan Turpin, Liquan Wang, Eric Heiden +5
The study of hand-object interaction requires generating viable grasp poses for high-dimensional multi-finger models, often relying on analytic grasp synthesis which tends to produ…
Representing 3D Shapes with Probabilistic Directed Distance Fields
Tristan Aumentado-Armstrong, Stavros Tsogkas, Sven Dickinson +1
Differentiable rendering is an essential operation in modern vision, allowing inverse graphics approaches to 3D understanding to be utilized in modern machine learning frameworks.…
GIFT: Generalizable Interaction-aware Functional Tool Affordances without Labels
Dylan Turpin, Liquan Wang, Stavros Tsogkas +2
Tool use requires reasoning about the fit between an object's affordances and the demands of a task. Visual affordance learning can benefit from goal-directed interaction experienc…
Disentangling Geometric Deformation Spaces in Generative Latent Shape Models
Tristan Aumentado-Armstrong, Stavros Tsogkas, Sven Dickinson +1
A complete representation of 3D objects requires characterizing the space of deformations in an interpretable manner, from articulations of a single instance to changes in shape ac…
Appearance Shock Grammar for Fast Medial Axis Extraction from Real Images
Charles-Olivier Dufresne Camaro, Morteza Rezanejad, Stavros Tsogkas +2
We combine ideas from shock graph theory with more recent appearance-based methods for medial axis extraction from complex natural scenes, improving upon the present best unsupervi…
Geometric Disentanglement for Generative Latent Shape Models
Tristan Aumentado-Armstrong, Stavros Tsogkas, Allan Jepson +1
Representing 3D shape is a fundamental problem in artificial intelligence, which has numerous applications within computer vision and graphics. One avenue that has recently begun t…