9 citations · 13 across the 2 of their papers we have counts for
5 papers
Local Implicit Grid Representations for 3D Scenes
Chiyu Max Jiang, Avneesh Sud, Ameesh Makadia +3
Shape priors learned from data are commonly used to reconstruct 3D objects from partial or noisy data. Yet no such shape priors are available for indoor scenes, since typical 3D au…
Local Deep Implicit Functions for 3D Shape
Kyle Genova, Forrester Cole, Avneesh Sud +2
The goal of this project is to learn a 3D shape representation that enables accurate surface reconstruction, compact storage, efficient computation, consistency for similar shapes,…
Latent feature disentanglement for 3D meshes
Jake Levinson, Avneesh Sud, Ameesh Makadia
Generative modeling of 3D shapes has become an important problem due to its relevance to many applications across Computer Vision, Graphics, and VR. In this paper we build upon rec…
Cross-Domain 3D Equivariant Image Embeddings
Carlos Esteves, Avneesh Sud, Zhengyi Luo +2
Spherical convolutional networks have been introduced recently as tools to learn powerful feature representations of 3D shapes. Spherical CNNs are equivariant to 3D rotations makin…
Eyemotion: Classifying facial expressions in VR using eye-tracking cameras
Steven Hickson, Nick Dufour, Avneesh Sud +2
One of the main challenges of social interaction in virtual reality settings is that head-mounted displays occlude a large portion of the face, blocking facial expressions and ther…