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06/10/2023
Aria Digital Twin: A New Benchmark Dataset for Egocentric 3D Machine Perception
We introduce the Aria Digital Twin (ADT) - an egocentric dataset capture...
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05/11/2020
FroDO: From Detections to 3D Objects
Object-oriented maps are important for scene understanding since they jo...
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08/18/2019
Distill Knowledge from NRSfM for Weakly Supervised 3D Pose Learning
We propose to learn a 3D pose estimator by distilling knowledge from Non...
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07/30/2019
Deep Non-Rigid Structure from Motion
Non-Rigid Structure from Motion (NRSfM) refers to the problem of reconst...
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02/28/2019
Deep Interpretable Non-Rigid Structure from Motion
All current non-rigid structure from motion (NRSfM) algorithms are limit...
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12/07/2017
Take it in your stride: Do we need striding in CNNs?
Since their inception, CNNs have utilized some type of striding operator...
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12/07/2017
CNNs are Globally Optimal Given Multi-Layer Support
Stochastic Gradient Descent (SGD) is the central workhorse for training ...
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11/29/2017
Image2Mesh: A Learning Framework for Single Image 3D Reconstruction
One challenge that remains open in 3D deep learning is how to efficientl...
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07/23/2017
Compact Model Representation for 3D Reconstruction
3D reconstruction from 2D images is a central problem in computer vision...
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06/21/2017
Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction
Conventional methods of 3D object generative modeling learn volumetric p...
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02/28/2015