Jingwei Huang

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Stanford University

ShapeFlow: Learnable Deformations Among 3D Shapes

We present ShapeFlow, a flow-based model for learning a deformation spac...
06/14/2020 ∙ by Chiyu "Max" Jiang, et al. ∙ 0 ∙ share

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ManifoldPlus: A Robust and Scalable Watertight Manifold Surface Generation Method for Triangle Soups

We present ManifoldPlus, a method for robust and scalable conversion of ...
05/23/2020 ∙ by Jingwei Huang, et al. ∙ 0 ∙ share

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MeshODE: A Robust and Scalable Framework for Mesh Deformation

We present MeshODE, a scalable and robust framework for pairwise CAD mod...
05/23/2020 ∙ by Jingwei Huang, et al. ∙ 0 ∙ share

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Deformation-Aware 3D Model Embedding and Retrieval

We introduce a new problem of retrieving 3D models that are deformable t...
04/02/2020 ∙ by Mikaela Angelina Uy, et al. ∙ 2 ∙ share

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Local Implicit Grid Representations for 3D Scenes

Shape priors learned from data are commonly used to reconstruct 3D objec...
03/19/2020 ∙ by Chiyu "Max" Jiang, et al. ∙ 44 ∙ share

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Adversarial Texture Optimization from RGB-D Scans

Realistic color texture generation is an important step in RGB-D surface...
03/18/2020 ∙ by Jingwei Huang, et al. ∙ 7 ∙ share

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Towards Digital Engineering – The Advent of Digital Systems Engineering

Digital Engineering, the digital transformation of engineering to levera...
02/21/2020 ∙ by Jingwei Huang, et al. ∙ 0 ∙ share

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NeurVPS: Neural Vanishing Point Scanning via Conic Convolution

We present a simple yet effective end-to-end trainable deep network with...
10/14/2019 ∙ by Yichao Zhou, et al. ∙ 0 ∙ share

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FrameNet: Learning Local Canonical Frames of 3D Surfaces from a Single RGB Image

In this work, we introduce the novel problem of identifying dense canoni...
03/29/2019 ∙ by Jingwei Huang, et al. ∙ 4 ∙ share

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Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

The goal of this paper is to estimate the 6D pose and dimensions of unse...
01/09/2019 ∙ by He Wang, et al. ∙ 16 ∙ share

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Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation

Convolutional Neural Networks (CNN) have been successful in processing d...
01/07/2019 ∙ by Chiyu "Max" Jiang, et al. ∙ 8 ∙ share

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Spherical CNNs on Unstructured Grids

We present an efficient convolution kernel for Convolutional Neural Netw...
01/07/2019 ∙ by Chiyu "Max" Jiang, et al. ∙ 14 ∙ share

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TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes

We introduce, TextureNet, a neural network architecture designed to extr...
11/30/2018 ∙ by Jingwei Huang, et al. ∙ 0 ∙ share

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Robust Watertight Manifold Surface Generation Method for ShapeNet Models

In this paper, we describe a robust algorithm for 2-Manifold generation ...
02/05/2018 ∙ by Jingwei Huang, et al. ∙ 0 ∙ share

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Jingwei Huang

Featured Co-authors

Bin Wang

Matthias Nießner

Hao Su

Leonidas Guibas

Thomas Funkhouser

Yi Ma

Leonidas J. Guibas

Prabhat

He Wang

Shuran Song

Li Yi

ShapeFlow: Learnable Deformations Among 3D Shapes

ManifoldPlus: A Robust and Scalable Watertight Manifold Surface Generation Method for Triangle Soups

MeshODE: A Robust and Scalable Framework for Mesh Deformation

Deformation-Aware 3D Model Embedding and Retrieval

Local Implicit Grid Representations for 3D Scenes

Adversarial Texture Optimization from RGB-D Scans

Towards Digital Engineering – The Advent of Digital Systems Engineering

NeurVPS: Neural Vanishing Point Scanning via Conic Convolution

FrameNet: Learning Local Canonical Frames of 3D Surfaces from a Single RGB Image

Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation

Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation

Spherical CNNs on Unstructured Grids

TextureNet: Consistent Local Parametrizations for Learning from High-Resolution Signals on Meshes

Robust Watertight Manifold Surface Generation Method for ShapeNet Models