269 citations · 594 across the 10 of their papers we have counts for
11 papers
Neural Fields in Visual Computing and Beyond
Yiheng Xie, Towaki Takikawa, Shunsuke Saito +7
Recent advances in machine learning have created increasing interest in solving visual computing problems using a class of coordinate-based neural networks that parametrize physica…
DRACO: Weakly Supervised Dense Reconstruction And Canonicalization of Objects
Rahul Sajnani, AadilMehdi Sanchawala, Krishna Murthy Jatavallabhula +2
We present DRACO, a method for Dense Reconstruction And Canonicalization of Object shape from one or more RGB images. Canonical shape reconstruction, estimating 3D object shape in…
Pix2Surf: Learning Parametric 3D Surface Models of Objects from Images
Jiahui Lei, Srinath Sridhar, Paul Guerrero +3
We investigate the problem of learning to generate 3D parametric surface representations for novel object instances, as seen from one or more views. Previous work on learning shape…
CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations
Davis Rempe, Tolga Birdal, Yongheng Zhao +3
We propose CaSPR, a method to learn object-centric Canonical Spatiotemporal Point Cloud Representations of dynamically moving or evolving objects. Our goal is to enable information…
Representation Learning Through Latent Canonicalizations
Or Litany, Ari Morcos, Srinath Sridhar +2
We seek to learn a representation on a large annotated data source that generalizes to a target domain using limited new supervision. Many prior approaches to this problem have foc…
Continuous Geodesic Convolutions for Learning on 3D Shapes
Zhangsihao Yang, Or Litany, Tolga Birdal +2
The majority of descriptor-based methods for geometric processing of non-rigid shape rely on hand-crafted descriptors. Recently, learning-based techniques have been shown effective…
Multiview Aggregation for Learning Category-Specific Shape Reconstruction
Srinath Sridhar, Davis Rempe, Julien Valentin +2
We investigate the problem of learning category-specific 3D shape reconstruction from a variable number of RGB views of previously unobserved object instances. Most approaches for…
Learning Generalizable Physical Dynamics of 3D Rigid Objects
Davis Rempe, Srinath Sridhar, He Wang +1
Humans have a remarkable ability to predict the effect of physical interactions on the dynamics of objects. Endowing machines with this ability would allow important applications i…
GANerated Hands for Real-time 3D Hand Tracking from Monocular RGB
Franziska Mueller, Florian Bernard, Oleksandr Sotnychenko +4
We address the highly challenging problem of real-time 3D hand tracking based on a monocular RGB-only sequence. Our tracking method combines a convolutional neural network with a k…
Real-time Hand Tracking under Occlusion from an Egocentric RGB-D Sensor
Franziska Mueller, Dushyant Mehta, Oleksandr Sotnychenko +3
We present an approach for real-time, robust and accurate hand pose estimation from moving egocentric RGB-D cameras in cluttered real environments. Existing methods typically fail…
Fast and Robust Hand Tracking Using Detection-Guided Optimization
Srinath Sridhar, Franziska Mueller, Antti Oulasvirta +1
Markerless tracking of hands and fingers is a promising enabler for human-computer interaction. However, adoption has been limited because of tracking inaccuracies, incomplete cove…