Search Results for author: Jun Gao

Found 55 papers, 21 papers with code

Bayesian-Boosted MetaLoc: Efficient Training and Guaranteed Generalization for Indoor Localization

no code implementations28 Aug 2023 Dongze Wu, Jun Gao, Feng Yin

Existing localization approaches utilizing environment-specific channel state information (CSI) excel under specific environment but struggle to generalize across varied environments.

Indoor Localization Meta-Learning

Flexible Isosurface Extraction for Gradient-Based Mesh Optimization

no code implementations10 Aug 2023 Tianchang Shen, Jacob Munkberg, Jon Hasselgren, Kangxue Yin, Zian Wang, Wenzheng Chen, Zan Gojcic, Sanja Fidler, Nicholas Sharp, Jun Gao

This work considers gradient-based mesh optimization, where we iteratively optimize for a 3D surface mesh by representing it as the isosurface of a scalar field, an increasingly common paradigm in applications including photogrammetry, generative modeling, and inverse physics.

Deblurring Masked Autoencoder is Better Recipe for Ultrasound Image Recognition

1 code implementation14 Jun 2023 Qingbo Kang, Jun Gao, Kang Li, Qicheng Lao

Overall, our work highlights the potential of MAE for ultrasound image recognition and presents a novel approach that incorporates deblurring to further improve its effectiveness.

Deblurring Image Classification

A Diffusion Model for Event Skeleton Generation

1 code implementation27 May 2023 Fangqi Zhu, Lin Zhang, Jun Gao, Bing Qin, Ruifeng Xu, Haiqin Yang

Event skeleton generation, aiming to induce an event schema skeleton graph with abstracted event nodes and their temporal relations from a set of event instance graphs, is a critical step in the temporal complex event schema induction task.

Denoising Graph Generation

Progressive Learning of 3D Reconstruction Network from 2D GAN Data

no code implementations18 May 2023 Aysegul Dundar, Jun Gao, Andrew Tao, Bryan Catanzaro

In this work, to overcome these limitations of generated datasets, we have two main contributions which lead us to achieve state-of-the-art results on challenging objects: 1) A robust multi-stage learning scheme that gradually relies more on the models own predictions when calculating losses, 2) A novel adversarial learning pipeline with online pseudo-ground truth generations to achieve fine details.

3D Reconstruction

Neural Fields meet Explicit Geometric Representation for Inverse Rendering of Urban Scenes

no code implementations6 Apr 2023 Zian Wang, Tianchang Shen, Jun Gao, Shengyu Huang, Jacob Munkberg, Jon Hasselgren, Zan Gojcic, Wenzheng Chen, Sanja Fidler

Reconstruction and intrinsic decomposition of scenes from captured imagery would enable many applications such as relighting and virtual object insertion.

3D Reconstruction Inverse Rendering

Exploring the Feasibility of ChatGPT for Event Extraction

no code implementations7 Mar 2023 Jun Gao, Huan Zhao, Changlong Yu, Ruifeng Xu

While ChatGPT has demonstrated impressive results in tasks like machine translation, text summarization, and question answering, it presents challenges when used for complex tasks like event extraction.

Event Extraction Machine Translation +2

A Generative Approach for Script Event Prediction via Contrastive Fine-tuning

1 code implementation7 Dec 2022 Fangqi Zhu, Jun Gao, Changlong Yu, Wei Wang, Chen Xu, Xin Mu, Min Yang, Ruifeng Xu

First, the pretrained language models adopted by current works ignore event-level knowledge, resulting in an inability to capture the correlations between events well.

Language Modelling

Magic3D: High-Resolution Text-to-3D Content Creation

1 code implementation CVPR 2023 Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, Tsung-Yi Lin

DreamFusion has recently demonstrated the utility of a pre-trained text-to-image diffusion model to optimize Neural Radiance Fields (NeRF), achieving remarkable text-to-3D synthesis results.

Text to 3D Vocal Bursts Intensity Prediction

MetaLoc: Learning to Learn Wireless Localization

no code implementations8 Nov 2022 Jun Gao, Dongze Wu, Feng Yin, Qinglei Kong, Lexi Xu, Shuguang Cui

The framework introduces two paradigms for the optimization of meta-parameters: a centralized paradigm that simplifies the process by sharing data from all historical environments, and a distributed paradigm that maintains data privacy by training meta-parameters for each specific environment separately.


TASA: Deceiving Question Answering Models by Twin Answer Sentences Attack

1 code implementation27 Oct 2022 Yu Cao, Dianqi Li, Meng Fang, Tianyi Zhou, Jun Gao, Yibing Zhan, DaCheng Tao

We present Twin Answer Sentences Attack (TASA), an adversarial attack method for question answering (QA) models that produces fluent and grammatical adversarial contexts while maintaining gold answers.

Adversarial Attack Question Answering

GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images

3 code implementations22 Sep 2022 Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, Sanja Fidler

As several industries are moving towards modeling massive 3D virtual worlds, the need for content creation tools that can scale in terms of the quantity, quality, and diversity of 3D content is becoming evident.

Improving Semantic Segmentation in Transformers using Hierarchical Inter-Level Attention

no code implementations5 Jul 2022 Gary Leung, Jun Gao, Xiaohui Zeng, Sanja Fidler

HILA extends hierarchical vision transformer architectures by adding local connections between features of higher and lower levels to the backbone encoder.

Semantic Segmentation

Model Degradation Hinders Deep Graph Neural Networks

1 code implementation9 Jun 2022 Wentao Zhang, Zeang Sheng, Ziqi Yin, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui

Graph Neural Networks (GNNs) have achieved great success in various graph mining tasks. However, drastic performance degradation is always observed when a GNN is stacked with many layers.

Graph Mining

Interpretable Proof Generation via Iterative Backward Reasoning

1 code implementation NAACL 2022 Hanhao Qu, Yu Cao, Jun Gao, Liang Ding, Ruifeng Xu

We present IBR, an Iterative Backward Reasoning model to solve the proof generation tasks on rule-based Question Answering (QA), where models are required to reason over a series of textual rules and facts to find out the related proof path and derive the final answer.

Question Answering

Empathetic Response Generation with State Management

1 code implementation7 May 2022 YuHan Liu, Jun Gao, Jiachen Du, Lanjun Zhou, Ruifeng Xu

The emotion-aware dialogue management contains two parts: (1) Emotion state tracking maintains the current emotion state of the user and (2) Empathetic dialogue policy selection predicts a target emotion and a user's intent based on the results of the emotion state tracking.

Dialogue Management Empathetic Response Generation +3

Fine Detailed Texture Learning for 3D Meshes with Generative Models

no code implementations17 Mar 2022 Aysegul Dundar, Jun Gao, Andrew Tao, Bryan Catanzaro

The reconstruction is posed as an adaptation problem and is done progressively where in the first stage, we focus on learning accurate geometry, whereas in the second stage, we focus on learning the texture with a generative adversarial network.

Extracting Triangular 3D Models, Materials, and Lighting From Images

2 code implementations CVPR 2022 Jacob Munkberg, Jon Hasselgren, Tianchang Shen, Jun Gao, Wenzheng Chen, Alex Evans, Thomas Müller, Sanja Fidler

We present an efficient method for joint optimization of topology, materials and lighting from multi-view image observations.

Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesis

no code implementations NeurIPS 2021 Tianchang Shen, Jun Gao, Kangxue Yin, Ming-Yu Liu, Sanja Fidler

The core of DMTet includes a deformable tetrahedral grid that encodes a discretized signed distance function and a differentiable marching tetrahedra layer that converts the implicit signed distance representation to the explicit surface mesh representation.

3DStyleNet: Creating 3D Shapes with Geometric and Texture Style Variations

no code implementations ICCV 2021 Kangxue Yin, Jun Gao, Maria Shugrina, Sameh Khamis, Sanja Fidler

Given a small set of high-quality textured objects, our method can create many novel stylized shapes, resulting in effortless 3D content creation and style-ware data augmentation.

3D Reconstruction Data Augmentation +1

Evaluating Deep Graph Neural Networks

1 code implementation2 Aug 2021 Wentao Zhang, Zeang Sheng, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui

Based on the experimental results, we answer the following two essential questions: (1) what actually leads to the compromised performance of deep GNNs; (2) when we need and how to build deep GNNs.

Graph Mining Node Classification

REAM$\sharp$: An Enhancement Approach to Reference-based Evaluation Metrics for Open-domain Dialog Generation

no code implementations30 May 2021 Jun Gao, Wei Bi, Ruifeng Xu, Shuming Shi

We first clarify an assumption on reference-based metrics that, if more high-quality references are added into the reference set, the reliability of the metric will increase.

Open-Domain Dialog

DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort

2 code implementations CVPR 2021 Yuxuan Zhang, Huan Ling, Jun Gao, Kangxue Yin, Jean-Francois Lafleche, Adela Barriuso, Antonio Torralba, Sanja Fidler

To showcase the power of our approach, we generated datasets for 7 image segmentation tasks which include pixel-level labels for 34 human face parts, and 32 car parts.

Image Segmentation Semantic Segmentation

Learning Deformable Tetrahedral Meshes for 3D Reconstruction

1 code implementation NeurIPS 2020 Jun Gao, Wenzheng Chen, Tommy Xiang, Clement Fuji Tsang, Alec Jacobson, Morgan McGuire, Sanja Fidler

We introduce Deformable Tetrahedral Meshes (DefTet) as a particular parameterization that utilizes volumetric tetrahedral meshes for the reconstruction problem.

3D Reconstruction

Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering

no code implementations ICLR 2021 Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao, Yinan Zhang, Antonio Torralba, Sanja Fidler

Key to our approach is to exploit GANs as a multi-view data generator to train an inverse graphics network using an off-the-shelf differentiable renderer, and the trained inverse graphics network as a teacher to disentangle the GAN's latent code into interpretable 3D properties.

Neural Rendering

Information Laundering for Model Privacy

no code implementations ICLR 2021 Xinran Wang, Yu Xiang, Jun Gao, Jie Ding

In this work, we propose information laundering, a novel framework for enhancing model privacy.

Interactive Annotation of 3D Object Geometry using 2D Scribbles

no code implementations ECCV 2020 Tianchang Shen, Jun Gao, Amlan Kar, Sanja Fidler

We implement our framework as a web service and conduct a user study, where we show that user annotated data using our method effectively facilitates real-world learning tasks.

Beyond Fixed Grid: Learning Geometric Image Representation with a Deformable Grid

no code implementations ECCV 2020 Jun Gao, Zian Wang, Jinchen Xuan, Sanja Fidler

We also utilize DefGrid at the output layers for the task of object mask annotation, and show that reasoning about object boundaries on our predicted polygonal grid leads to more accurate results over existing pixel-wise and curve-based approaches.

Semantic Segmentation

Quantum Computation for Pricing the Collateralized Debt Obligations

no code implementations6 Aug 2020 Hao Tang, Anurag Pal, Lu-Feng Qiao, Tian-Yu Wang, Jun Gao, Xian-Min Jin

Collateralized debt obligation (CDO) has been one of the most commonly used structured financial products and is intensively studied in quantitative finance.

EPI-based Oriented Relation Networks for Light Field Depth Estimation

1 code implementation9 Jul 2020 Kunyuan Li, Jun Zhang, Rui Sun, Xu-Dong Zhang, Jun Gao

Based on the observation that an oriented line and its neighboring pixels in an EPI share a similar linear structure, we propose an end-to-end fully convolutional network (FCN) to estimate the depth value of the intersection point on the horizontal and vertical EPIs.

Data Augmentation Depth Estimation

A Discrete CVAE for Response Generation on Short-Text Conversation

no code implementations IJCNLP 2019 Jun Gao, Wei Bi, Xiaojiang Liu, Junhui Li, Guodong Zhou, Shuming Shi

In this paper, we introduce a discrete latent variable with an explicit semantic meaning to improve the CVAE on short-text conversation.

Response Generation Short-Text Conversation +1

Omni SCADA Intrusion Detection Using Deep Learning Algorithms

no code implementations6 Aug 2019 Jun Gao, Luyun Gan, Fabiola Buschendorf, Liao Zhang, Hua Liu, Peixue Li, Xiaodai Dong, Tao Lu

We investigate deep learning based omni intrusion detection system (IDS) for supervisory control and data acquisition (SCADA) networks that are capable of detecting both temporally uncorrelated and correlated attacks.

Intrusion Detection

Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer

1 code implementation NeurIPS 2019 Wenzheng Chen, Jun Gao, Huan Ling, Edward J. Smith, Jaakko Lehtinen, Alec Jacobson, Sanja Fidler

Many machine learning models operate on images, but ignore the fact that images are 2D projections formed by 3D geometry interacting with light, in a process called rendering.

Single-View 3D Reconstruction

Representation Degeneration Problem in Training Natural Language Generation Models

no code implementations ICLR 2019 Jun Gao, Di He, Xu Tan, Tao Qin, Li-Wei Wang, Tie-Yan Liu

We study an interesting problem in training neural network-based models for natural language generation tasks, which we call the \emph{representation degeneration problem}.

Language Modelling Machine Translation +3

Fine-Grained Sentence Functions for Short-Text Conversation

no code implementations ACL 2019 Wei Bi, Jun Gao, Xiaojiang Liu, Shuming Shi

Classification models are trained on this dataset to (i) recognize the sentence function of new data in a large corpus of short-text conversations; (ii) estimate a proper sentence function of the response given a test query.

Information Retrieval Retrieval +1

Personalized Bundle List Recommendation

no code implementations3 Apr 2019 Jinze Bai, Chang Zhou, Junshuai Song, Xiaoru Qu, Weiting An, Zhao Li, Jun Gao

In particular, BGN improves the precision of the best competitors by 16\% on average while maintaining the highest diversity on four datasets, and yields a 3. 85x improvement of response time over the best competitors in the bundle list recommendation problem.

Marketing Point Processes +1

Mimicking the In-Camera Color Pipeline for Camera-Aware Object Compositing

no code implementations27 Mar 2019 Jun Gao, Xiao Li, Li-Wei Wang, Sanja Fidler, Stephen Lin

We present a method for compositing virtual objects into a photograph such that the object colors appear to have been processed by the photo's camera imaging pipeline.

Fast Interactive Object Annotation with Curve-GCN

2 code implementations CVPR 2019 Huan Ling, Jun Gao, Amlan Kar, Wenzheng Chen, Sanja Fidler

Our model runs at 29. 3ms in automatic, and 2. 6ms in interactive mode, making it 10x and 100x faster than Polygon-RNN++.

DeepSpline: Data-Driven Reconstruction of Parametric Curves and Surfaces

2 code implementations12 Jan 2019 Jun Gao, Chengcheng Tang, Vignesh Ganapathi-Subramanian, Jiahui Huang, Hao Su, Leonidas J. Guibas

Reconstruction of geometry based on different input modes, such as images or point clouds, has been instrumental in the development of computer aided design and computer graphics.

Generating Multiple Diverse Responses for Short-Text Conversation

no code implementations14 Nov 2018 Jun Gao, Wei Bi, Xiaojiang Liu, Junhui Li, Shuming Shi

In this paper, we propose a novel response generation model, which considers a set of responses jointly and generates multiple diverse responses simultaneously.

Informativeness Response Generation +1

Towards Less Generic Responses in Neural Conversation Models: A Statistical Re-weighting Method

1 code implementation EMNLP 2018 Yahui Liu, Wei Bi, Jun Gao, Xiaojiang Liu, Jian Yao, Shuming Shi

We observe that in the conversation tasks, each query could have multiple responses, which forms a 1-to-n or m-to-n relationship in the view of the total corpus.

Dialogue Generation Machine Translation +1

Learning to Navigate for Fine-grained Classification

9 code implementations ECCV 2018 Ze Yang, Tiange Luo, Dong Wang, Zhiqiang Hu, Jun Gao, Li-Wei Wang

In consideration of intrinsic consistency between informativeness of the regions and their probability being ground-truth class, we design a novel training paradigm, which enables Navigator to detect most informative regions under the guidance from Teacher.

Fine-Grained Image Classification General Classification +1

Integrated Server for Measurement-Device-Independent Quantum Key Distribution Network

no code implementations26 Aug 2018 Ci-Yu Wang, Jun Gao, Zhi-Qiang Jiao, Lu-Feng Qiao, Ruo-Jing Ren, Zhen Feng, Yuan Chen, Zeng-Quan Yan, Yao Wang, Hao Tang, Xian-Min Jin

Quantum key distribution (QKD), harnessing quantum physics and optoelectronics, may promise unconditionally secure information exchange in theory.

Quantum Physics

Direct Mapping Hidden Excited State Interaction Patterns from ab initio Dynamics and Its Implications on Force Field Development

no code implementations28 May 2017 Fang Liu, Likai Du, Dongju Zhang, Jun Gao

Based on the knowledge of these meta-stable patterns, we suggested an interpolation scheme with only a concrete and finite set of known patterns to accurately predict the ground and excited state properties of the entire dynamics trajectories.

Clustering Time Series +1

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