Jingwei Huang

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Stanford University

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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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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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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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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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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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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Deformation-Aware 3D Model Embedding and Retrieval

We introduce a new problem of retrieving 3D models that are not just sim...
04/02/2020 ∙ by Mikaela Angelina Uy, et al. ∙ 2 ∙ 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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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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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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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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Jingwei Huang

Featured Co-authors

Hao Su

Matthias Nießner

Leonidas Guibas

Thomas Funkhouser

Leonidas J. Guibas

Prabhat

Yi Ma

Shuran Song

He Wang

Li Yi

Angela Dai

Local Implicit Grid Representations for 3D Scenes

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

Spherical CNNs on Unstructured Grids

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

Adversarial Texture Optimization from RGB-D Scans

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

Deformation-Aware 3D Model Embedding and Retrieval

Robust Watertight Manifold Surface Generation Method for ShapeNet Models

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

NeurVPS: Neural Vanishing Point Scanning via Conic Convolution

Towards Digital Engineering – The Advent of Digital Systems Engineering