Search Results for author: Jingwei Huang

Found 27 papers, 18 papers with code

SAI3D: Segment Any Instance in 3D Scenes

no code implementations17 Dec 2023 Yingda Yin, Yuzheng Liu, Yang Xiao, Daniel Cohen-Or, Jingwei Huang, Baoquan Chen

Advancements in 3D instance segmentation have traditionally been tethered to the availability of annotated datasets, limiting their application to a narrow spectrum of object categories.

3D Instance Segmentation Scene Parsing +2

Digital Engineering Transformation with Trustworthy AI towards Industry 4.0: Emerging Paradigm Shifts

no code implementations3 Jan 2023 Jingwei Huang

Digital engineering transformation is a crucial process for the engineering paradigm shifts in the fourth industrial revolution (4IR), and artificial intelligence (AI) is a critical enabling technology in digital engineering transformation.

Regularized Primitive Graph Learning for Unified Vector Mapping

no code implementations ICCV 2023 Lei Wang, Min Dai, Jianan He, Jingwei Huang

Our key idea is using primitive graph as a unified representation of vector maps and formulating shape regularization and topology reconstruction as primitive graph reconstruction problems that can be solved in the same framework.

Graph Learning Graph Reconstruction

LeaF: Learning Frames for 4D Point Cloud Sequence Understanding

no code implementations ICCV 2023 Yunze Liu, Junyu Chen, Zekai Zhang, Jingwei Huang, Li Yi

With such frames, we can factorize geometry and motion to facilitate a feature-space geometric reconstruction for more effective 4D learning.


Primitive Graph Learning for Unified Vector Mapping

no code implementations28 Jun 2022 Lei Wang, Min Dai, Jianan He, Jingwei Huang, Mingwei Sun

Then, we convert vector shape prediction, regularization, and topology reconstruction into a unique primitive graph learning problem.

Graph Learning

Reinforcement learning for automatic quadrilateral mesh generation: a soft actor-critic approach

1 code implementation19 Mar 2022 Jie Pan, Jingwei Huang, Gengdong Cheng, Yong Zeng

This paper proposes, implements, and evaluates a reinforcement learning (RL)-based computational framework for automatic mesh generation.

reinforcement-learning Reinforcement Learning (RL)

MVLayoutNet:3D layout reconstruction with multi-view panoramas

no code implementations12 Dec 2021 Zhihua Hu, Bo Duan, Yanfeng Zhang, Mingwei Sun, Jingwei Huang

We jointly train a layout module to produce an initial layout and a novel MVS module to obtain accurate layout geometry.

3D Reconstruction

Intelligent Agent for Hurricane Emergency Identification and Text Information Extraction from Streaming Social Media Big Data

no code implementations14 Jun 2021 Jingwei Huang, Wael Khallouli, Ghaith Rabadi, Mamadou Seck

This paper presents our research on leveraging social media Big Data and AI to support hurricane disaster emergency response.

ShapeFlow: Learnable Deformation Flows Among 3D Shapes

no code implementations NeurIPS 2020 Chiyu Jiang, Jingwei Huang, Andrea Tagliasacchi, Leonidas J. Guibas

Such a space naturally allows the disentanglement of geometric style (coming from the source) and structural pose (conforming to the target).

Disentanglement Style Transfer

ShapeFlow: Learnable Deformations Among 3D Shapes

1 code implementation14 Jun 2020 Chiyu "Max" Jiang, Jingwei Huang, Andrea Tagliasacchi, Leonidas Guibas

We illustrate the effectiveness of this learned deformation space for various downstream applications, including shape generation via deformation, geometric style transfer, unsupervised learning of a consistent parameterization for entire classes of shapes, and shape interpolation.

Disentanglement Style Transfer

MeshODE: A Robust and Scalable Framework for Mesh Deformation

1 code implementation23 May 2020 Jingwei Huang, Chiyu Max Jiang, Baiqiang Leng, Bin Wang, Leonidas Guibas

Given a pair of shapes, our framework provides a novel shape feature-preserving mapping function that continuously deforms one model to the other by minimizing fitting and rigidity losses based on the non-rigid iterative-closest-point (ICP) algorithm.

Graphics Computational Geometry

Deformation-Aware 3D Model Embedding and Retrieval

1 code implementation ECCV 2020 Mikaela Angelina Uy, Jingwei Huang, Minhyuk Sung, Tolga Birdal, Leonidas Guibas

We introduce a new problem of retrieving 3D models that are deformable to a given query shape and present a novel deep deformation-aware embedding to solve this retrieval task.

3D Object Reconstruction Metric Learning +1

Local Implicit Grid Representations for 3D Scenes

1 code implementation19 Mar 2020 Chiyu Max Jiang, Avneesh Sud, Ameesh Makadia, Jingwei Huang, Matthias Nießner, Thomas Funkhouser

Then, we use the decoder as a component in a shape optimization that solves for a set of latent codes on a regular grid of overlapping crops such that an interpolation of the decoded local shapes matches a partial or noisy observation.

3D Shape Representation Surface Reconstruction

Adversarial Texture Optimization from RGB-D Scans

1 code implementation CVPR 2020 Jingwei Huang, Justus Thies, Angela Dai, Abhijit Kundu, Chiyu Max Jiang, Leonidas Guibas, Matthias Nießner, Thomas Funkhouser

In this work, we present a novel approach for color texture generation using a conditional adversarial loss obtained from weakly-supervised views.

Surface Reconstruction Texture Synthesis

NeurVPS: Neural Vanishing Point Scanning via Conic Convolution

1 code implementation NeurIPS 2019 Yichao Zhou, Haozhi Qi, Jingwei Huang, Yi Ma

We present a simple yet effective end-to-end trainable deep network with geometry-inspired convolutional operators for detecting vanishing points in images.

Camera Calibration

Spherical CNNs on Unstructured Grids

1 code implementation ICLR 2019 Chiyu "Max" Jiang, Jingwei Huang, Karthik Kashinath, Prabhat, Philip Marcus, Matthias Niessner

We present an efficient convolution kernel for Convolutional Neural Networks (CNNs) on unstructured grids using parameterized differential operators while focusing on spherical signals such as panorama images or planetary signals.

Semantic Segmentation

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

1 code implementation CVPR 2019 Jingwei Huang, Haotian Zhang, Li Yi, Thomas Funkhouser, Matthias Nießner, Leonidas Guibas

We introduce, TextureNet, a neural network architecture designed to extract features from high-resolution signals associated with 3D surface meshes (e. g., color texture maps).

3D Semantic Segmentation

Robust Watertight Manifold Surface Generation Method for ShapeNet Models

2 code implementations5 Feb 2018 Jingwei Huang, Hao Su, Leonidas Guibas

In this paper, we describe a robust algorithm for 2-Manifold generation of various kinds of ShapeNet Models.

Computational Geometry

Automatic Thumbnail Generation Based on Visual Representativeness and Foreground Recognizability

no code implementations ICCV 2015 Jingwei Huang, Huarong Chen, Bin Wang, Stephen Lin

We present an automatic thumbnail generation technique based on two essential considerations: how well they visually represent the original photograph, and how well the foreground can be recognized after the cropping and downsizing steps of thumbnailing.

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