Digital engineering transformation is a crucial process for the engineer...
This paper proposes a 4D backbone for long-term point cloud video
unders...
This paper proposes, implements, and evaluates a reinforcement learning
...
We present MVLayoutNet, an end-to-end network for holistic 3D reconstruc...
This paper presents our research on leveraging social media Big Data and...
We present HoliCity, a city-scale 3D dataset with rich structural
inform...
We present ShapeFlow, a flow-based model for learning a deformation spac...
We present ManifoldPlus, a method for robust and scalable conversion of
...
We present MeshODE, a scalable and robust framework for pairwise CAD mod...
We introduce a new problem of retrieving 3D models that are deformable t...
Shape priors learned from data are commonly used to reconstruct 3D objec...
Realistic color texture generation is an important step in RGB-D surface...
Digital Engineering, the digital transformation of engineering to levera...
We present a simple yet effective end-to-end trainable deep network with...
In this work, we introduce the novel problem of identifying dense canoni...
The goal of this paper is to estimate the 6D pose and dimensions of unse...
Convolutional Neural Networks (CNN) have been successful in processing d...
We present an efficient convolution kernel for Convolutional Neural Netw...
We introduce, TextureNet, a neural network architecture designed to extr...
In this paper, we describe a robust algorithm for 2-Manifold generation ...