Search Results for author: Peng Chen

Found 100 papers, 41 papers with code

ROSE: Register Assisted General Time Series Forecasting with Decomposed Frequency Learning

no code implementations24 May 2024 Yihang Wang, Yuying Qiu, Peng Chen, Kai Zhao, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo

Enabling general time series forecasting faces two challenges: how to obtain unified representations from multi-domian time series data, and how to capture domain-specific features from time series data across various domains for adaptive transfer in downstream tasks.

Time Series Time Series Forecasting

TIGER: Text-Instructed 3D Gaussian Retrieval and Coherent Editing

no code implementations23 May 2024 Teng Xu, Jiamin Chen, Peng Chen, Youjia Zhang, Junqing Yu, Wei Yang

Editing objects within a scene is a critical functionality required across a broad spectrum of applications in computer vision and graphics.


Movable Antennas Aided Multicast MISO Communication Systems

no code implementations12 May 2024 Zhenqiao Cheng, Nanxi Li, Ruizhe Long, Jianchi Zhu, Chongjun Ouyang, Peng Chen

A novel multicast communication system with movable antennas (MAs) is proposed, where the antenna position optimization is exploited to enhance the transmission rate.


CFMW: Cross-modality Fusion Mamba for Multispectral Object Detection under Adverse Weather Conditions

1 code implementation25 Apr 2024 Haoyuan Li, Qi Hu, You Yao, Kailun Yang, Peng Chen

Furthermore, we introduce the Cross-modality Fusion Mamba with Weather-removal (CFMW) to augment detection accuracy in adverse weather conditions.

Multispectral Object Detection Object +2

Adaptive Patching for High-resolution Image Segmentation with Transformers

no code implementations15 Apr 2024 Enzhi Zhang, Isaac Lyngaas, Peng Chen, Xiao Wang, Jun Igarashi, Yuankai Huo, Mohamed Wahib, Masaharu Munetomo

For high-resolution images, e. g. microscopic pathology images, the quadratic compute and memory cost prohibits the use of an attention-based model, if we are to use smaller patch sizes that are favorable in segmentation.

Friction Image Segmentation +2

Low-Complexity Estimation Algorithm and Decoupling Scheme for FRaC System

no code implementations27 Mar 2024 Mengjiang Sun, Peng Chen, Zhenxin Cao, Fei Shen

Hence, a novel decomposed decoupled atomic norm minimization (DANM) method is proposed by splitting the 3D-parameter estimating matrix into multiple 2D matrices with sparsity constraints.

Autonomous Vehicles

skscope: Fast Sparsity-Constrained Optimization in Python

1 code implementation27 Mar 2024 Zezhi Wang, Jin Zhu, Peng Chen, Huiyang Peng, Xiaoke Zhang, Anran Wang, Yu Zheng, Junxian Zhu, Xueqin Wang

Applying iterative solvers on sparsity-constrained optimization (SCO) requires tedious mathematical deduction and careful programming/debugging that hinders these solvers' broad impact.

Derivative-enhanced Deep Operator Network

no code implementations29 Feb 2024 Yuan Qiu, Nolan Bridges, Peng Chen

Deep operator networks (DeepONets), a class of neural operators that learn mappings between function spaces, have recently been developed as surrogate models for parametric partial differential equations (PDEs).

Dimensionality Reduction

Probabilistic Bayesian optimal experimental design using conditional normalizing flows

no code implementations28 Feb 2024 Rafael Orozco, Felix J. Herrmann, Peng Chen

Bayesian optimal experimental design (OED) seeks to conduct the most informative experiment under budget constraints to update the prior knowledge of a system to its posterior from the experimental data in a Bayesian framework.

Experimental Design

AlignMiF: Geometry-Aligned Multimodal Implicit Field for LiDAR-Camera Joint Synthesis

1 code implementation CVPR 2024 Tao Tang, Guangrun Wang, Yixing Lao, Peng Chen, Jie Liu, Liang Lin, Kaicheng Yu, Xiaodan Liang

Through extensive experiments across various datasets and scenes, we demonstrate the effectiveness of our approach in facilitating better interaction between LiDAR and camera modalities within a unified neural field.

Novel View Synthesis

Bring Your Own Character: A Holistic Solution for Automatic Facial Animation Generation of Customized Characters

1 code implementation21 Feb 2024 Zechen Bai, Peng Chen, Xiaolan Peng, Lu Liu, Hui Chen, Mike Zheng Shou, Feng Tian

In our solution, a deep learning model was first trained to retarget the facial expression from input face images to virtual human faces by estimating the blendshape coefficients.


Learning pseudo-contractive denoisers for inverse problems

no code implementations8 Feb 2024 Deliang Wei, Peng Chen, Fang Li

A training strategy based on holomorphic transformation and functional calculi is proposed to enforce the pseudo-contractive denoiser assumption.

Enabling Secure Wireless Communications via Movable Antennas

no code implementations21 Dec 2023 Zhenqiao Cheng, Nanxi Li, Jianchi Zhu, Xiaoming She, Chongjun Ouyang, Peng Chen

A pioneering secure transmission scheme is proposed, which harnesses movable antennas (MAs) to optimize antenna positions for augmenting the physical layer security.


DiffusionTalker: Personalization and Acceleration for Speech-Driven 3D Face Diffuser

no code implementations28 Nov 2023 Peng Chen, Xiaobao Wei, Ming Lu, Yitong Zhu, Naiming Yao, Xingyu Xiao, Hui Chen

To address the above limitations, we propose DiffusionTalker, a diffusion-based method that utilizes contrastive learning to personalize 3D facial animation and knowledge distillation to accelerate 3D animation generation.

3D Face Animation Contrastive Learning +1

Ultra-Long Sequence Distributed Transformer

no code implementations4 Nov 2023 Xiao Wang, Isaac Lyngaas, Aristeidis Tsaris, Peng Chen, Sajal Dash, Mayanka Chandra Shekar, Tao Luo, Hong-Jun Yoon, Mohamed Wahib, John Gouley

This paper presents a novel and efficient distributed training method, the Long Short-Sequence Transformer (LSS Transformer), for training transformer with long sequences.

BEVHeight++: Toward Robust Visual Centric 3D Object Detection

no code implementations28 Sep 2023 Lei Yang, Tao Tang, Jun Li, Peng Chen, Kun Yuan, Li Wang, Yi Huang, Xinyu Zhang, Kaicheng Yu

In essence, we regress the height to the ground to achieve a distance-agnostic formulation to ease the optimization process of camera-only perception methods.

3D Object Detection Autonomous Driving +2

NoncovANM: Gridless DOA Estimation for LPDF System

no code implementations25 Sep 2023 Yangying Zhao, Peng Chen, Zhenxin Cao, Xianbin Wang

High resolution DOA estimation requires large array aperture, which leads to the increase of hardware cost.

DNN-DANM: A High-Accuracy Two-Dimensional DOA Estimation Method Using Practical RIS

1 code implementation25 Sep 2023 Zhimin Chen, Peng Chen, Le Zheng, Yudong Zhang

After formulating the system model with the mutual coupling effect and the reflection phase/amplitude errors of the RIS, a novel DNNDANM method is proposed for the DOA estimation by combining the deep neural network (DNN) and the decoupling atomic norm minimization (DANM).

Movable Antenna-Empowered AirComp

no code implementations22 Sep 2023 Zhenqiao Cheng, Nanxi Li, Jianchi Zhu, Xiaoming She, Chongjun Ouyang, Peng Chen

A novel over-the-air computation (AirComp) framework, empowered by the incorporation of movable antennas (MAs), is proposed to significantly enhance computation accuracy.


Towards General and Efficient Online Tuning for Spark

no code implementations5 Sep 2023 Yang Li, Huaijun Jiang, Yu Shen, Yide Fang, Xiaofeng Yang, Danqing Huang, Xinyi Zhang, Wentao Zhang, Ce Zhang, Peng Chen, Bin Cui

The distributed data analytic system -- Spark is a common choice for processing massive volumes of heterogeneous data, while it is challenging to tune its parameters to achieve high performance.

Bayesian Optimization Meta-Learning

Using Adamic-Adar Index Algorithm to Predict Volunteer Collaboration: Less is More

no code implementations25 Aug 2023 Chao Wu, Peng Chen, Baiqiao Yin, Zijuan Lin, Chen Jiang, Di Yu, Changhong Zou, Chunwang Lui

Social networks exhibit a complex graph-like structure due to the uncertainty surrounding potential collaborations among participants.

Ensemble Learning Link Prediction

Efficient PDE-Constrained optimization under high-dimensional uncertainty using derivative-informed neural operators

1 code implementation31 May 2023 Dingcheng Luo, Thomas O'Leary-Roseberry, Peng Chen, Omar Ghattas

We propose a novel machine learning framework for solving optimization problems governed by large-scale partial differential equations (PDEs) with high-dimensional random parameters.

PRODIGY: Enabling In-context Learning Over Graphs

no code implementations NeurIPS 2023 Qian Huang, Hongyu Ren, Peng Chen, Gregor Kržmanc, Daniel Zeng, Percy Liang, Jure Leskovec

In-context learning is the ability of a pretrained model to adapt to novel and diverse downstream tasks by conditioning on prompt examples, without optimizing any parameters.

Graph Neural Network In-Context Learning +1

Cramer-Rao Lower Bound Analysis for OTFS and OFDM Modulation Systems

no code implementations27 Apr 2023 Bowen Wang, Jianchi Zhu, Xiaoming She, Peng Chen

The orthogonal time frequency space (OTFS) modulation as a promising signal representation attracts growingcinterest for integrated sensing and communication (ISAC), yet its merits over orthogonal frequency division multiplexing (OFDM) remain controversial.

Universal Adversarial Backdoor Attacks to Fool Vertical Federated Learning in Cloud-Edge Collaboration

no code implementations22 Apr 2023 Peng Chen, Xin Du, Zhihui Lu, Hongfeng Chai

To this end, we define a threat model for backdoor attacks in VFL and introduce a universal adversarial backdoor (UAB) attack to poison the predictions of VFL.

Binary Classification Vertical Federated Learning

LiDAR-NeRF: Novel LiDAR View Synthesis via Neural Radiance Fields

1 code implementation20 Apr 2023 Tang Tao, Longfei Gao, Guangrun Wang, Yixing Lao, Peng Chen, Hengshuang Zhao, Dayang Hao, Xiaodan Liang, Mathieu Salzmann, Kaicheng Yu

We address this challenge by formulating, to the best of our knowledge, the first differentiable end-to-end LiDAR rendering framework, LiDAR-NeRF, leveraging a neural radiance field (NeRF) to facilitate the joint learning of geometry and the attributes of 3D points.

3D Reconstruction Novel LiDAR View Synthesis +1

Internal Structure Attention Network for Fingerprint Presentation Attack Detection from Optical Coherence Tomography

no code implementations20 Mar 2023 Haohao Sun, Yilong Zhang, Peng Chen, Haixia Wang, Ronghua Liang

As a non-invasive optical imaging technique, optical coherence tomography (OCT) has proven promising for automatic fingerprint recognition system (AFRS) applications.

Domain Generalization

BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection

1 code implementation CVPR 2023 Lei Yang, Kaicheng Yu, Tao Tang, Jun Li, Kun Yuan, Li Wang, Xinyu Zhang, Peng Chen

In essence, instead of predicting the pixel-wise depth, we regress the height to the ground to achieve a distance-agnostic formulation to ease the optimization process of camera-only perception methods.

3D Object Detection Autonomous Driving +1

A Visual Representation-guided Framework with Global Affinity for Weakly Supervised Salient Object Detection

no code implementations21 Feb 2023 Binwei Xu, Haoran Liang, Weihua Gong, Ronghua Liang, Peng Chen

Fully supervised salient object detection (SOD) methods have made considerable progress in performance, yet these models rely heavily on expensive pixel-wise labels.

object-detection Object Detection +2

Low-Cost Beamforming and DOA Estimation Based on One-Bit Reconfigurable Intelligent Surface

no code implementations15 Nov 2022 Zihan Yang, Peng Chen, Ziyu Guo, Dahai Ni

In this work, we consider the Direction-of-Arrival (DOA) estimation problem in a low-cost architecture where only one antenna as the receiver is aided by a reconfigurable intelligent surface (RIS).

URGLQ: An Efficient Covariance Matrix Reconstruction Method for Robust Adaptive Beamforming

1 code implementation5 Oct 2022 Tao Luo, Peng Chen, Zhenxin Cao, Le Zheng, Zongxin Wang

The computational complexity of the conventional adaptive beamformer is relatively large, and the performance degrades significantly due to the model mismatch errors and the unwanted signals in received data.

Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning

1 code implementation21 Jun 2022 Thomas O'Leary-Roseberry, Peng Chen, Umberto Villa, Omar Ghattas

We propose derivative-informed neural operators (DINOs), a general family of neural networks to approximate operators as infinite-dimensional mappings from input function spaces to output function spaces or quantities of interest.

Dimensionality Reduction Experimental Design

Optimal Neural Network Approximation of Wasserstein Gradient Direction via Convex Optimization

1 code implementation26 May 2022 Yifei Wang, Peng Chen, Mert Pilanci, Wuchen Li

We study the variational problem in the family of two-layer networks with squared-ReLU activations, towards which we derive a semi-definite programming (SDP) relaxation.

Bayesian Inference

RIS-ADMM: A RIS and ADMM-Based Passive and Sparse Sensing Method With Interference Removal

1 code implementation25 May 2022 Peng Chen, Zhimin Chen, Pu Miao, Yun Chen

This letter addresses the passive sensing issue utilizing wireless communication signals and RIS amidst interference from wireless access points (APs).

Scalable Multi-view Clustering with Graph Filtering

1 code implementation18 May 2022 Liang Liu, Peng Chen, Guangchun Luo, Zhao Kang, Yonggang Luo, Sanchu Han

With the explosive growth of multi-source data, multi-view clustering has attracted great attention in recent years.

Attribute Clustering

Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction

no code implementations12 May 2022 Xiao Wang, Aristeidis Tsaris, Debangshu Mukherjee, Mohamed Wahib, Peng Chen, Mark Oxley, Olga Ovchinnikova, Jacob Hinkle

In this paper, we propose a novel image gradient decomposition method that significantly reduces the memory footprint for ptychographic reconstruction by tessellating image gradients and diffraction measurements into tiles.

A RIS-Based Vehicle DOA Estimation Method With Integrated Sensing and Communication System

1 code implementation25 Apr 2022 Zhimin Chen, Peng Chen, Ziyu Guo, Yudong Zhang, Xianbin Wang

A novel estimation method is proposed in the scenario with a receiver using only one full-functional channel, where multiple measurements for the DOA estimation are achieved by controlling the reflection matrix (measurement matrix) in the RIS.

Learning Video Salient Object Detection Progressively from Unlabeled Videos

1 code implementation5 Apr 2022 Binwei Xu, Haoran Liang, Wentian Ni, Weihua Gong, Ronghua Liang, Peng Chen

Recent deep learning-based video salient object detection (VSOD) has achieved some breakthrough, but these methods rely on expensive annotated videos with pixel-wise annotations, weak annotations, or part of the pixel-wise annotations.

Object object-detection +3

Efficient DOA Estimation Method for Reconfigurable Intelligent Surfaces Aided UAV Swarm

1 code implementation19 Mar 2022 Peng Chen, Zhimin Chen, Beixiong Zheng, Xianbin Wang

Specifically, considering the position perturbation of UAVs, a new atomic norm-based DOA estimation method is proposed, where an atomic norm is defined with the parameter of the position perturbation.


SDOA-Net: An Efficient Deep Learning-Based DOA Estimation Network for Imperfect Array

2 code implementations19 Mar 2022 Peng Chen, Zhimin Chen, Liang Liu, Yun Chen, Xianbin Wang

The estimation of direction of arrival (DOA) is a crucial issue in conventional radar, wireless communication, and integrated sensing and communication (ISAC) systems.


Reconfigurable Intelligent Surface Aided Sparse DOA Estimation Method With Non-ULA

no code implementations19 Mar 2022 Peng Chen, Zihan Yang, Zhimin Chen, Ziyu Guo

The direction of arrival (DOA) estimation problem is addressed in this letter.

Mesa: A Memory-saving Training Framework for Transformers

3 code implementations22 Nov 2021 Zizheng Pan, Peng Chen, Haoyu He, Jing Liu, Jianfei Cai, Bohan Zhuang

While Transformers have delivered significant performance improvements, training such networks is extremely memory intensive owing to storing all intermediate activations that are needed for gradient computation during backpropagation, especially for long sequences.


Looper: An end-to-end ML platform for product decisions

no code implementations14 Oct 2021 Igor L. Markov, Hanson Wang, Nitya Kasturi, Shaun Singh, Sze Wai Yuen, Mia Garrard, Sarah Tran, Yin Huang, Zehui Wang, Igor Glotov, Tanvi Gupta, Boshuang Huang, Peng Chen, Xiaowen Xie, Michael Belkin, Sal Uryasev, Sam Howie, Eytan Bakshy, Norm Zhou

Modern software systems and products increasingly rely on machine learning models to make data-driven decisions based on interactions with users, infrastructure and other systems.

Decision Making

Efficient Re-parameterization Residual Attention Network For Nonhomogeneous Image Dehazing

1 code implementation12 Sep 2021 Tian Ye, ErKang Chen, XinRui Huang, Peng Chen

This paper proposes an end-to-end Efficient Re-parameterizationResidual Attention Network(ERRA-Net) to directly restore the nonhomogeneous hazy image.

Image Dehazing Nonhomogeneous Image Dehazing

PermuteFormer: Efficient Relative Position Encoding for Long Sequences

1 code implementation EMNLP 2021 Peng Chen

Based on the analysis, we propose PermuteFormer, a Performer-based model with relative position encoding that scales linearly on long sequences.

Language Modelling Position

A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification

no code implementations30 Jul 2021 Xiangyun Li, Peng Chen, Zhanpeng Bao

The electroencephalography (EEG) signal is a non-stationary, stochastic, and highly non-linear bioelectric signal for which achieving high classification accuracy is challenging, especially when the number of subjects is limited.

EEG Motor Imagery +1

Smoothed Multi-View Subspace Clustering

1 code implementation18 Jun 2021 Peng Chen, Liang Liu, Zhengrui Ma, Zhao Kang

In recent years, multi-view subspace clustering has achieved impressive performance due to the exploitation of complementary imformation across multiple views.

Clustering Multi-view Subspace Clustering

ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spotting

1 code implementation8 May 2021 Yuliang Liu, Chunhua Shen, Lianwen Jin, Tong He, Peng Chen, Chongyu Liu, Hao Chen

Previous methods can be roughly categorized into two groups: character-based and segmentation-based, which often require character-level annotations and/or complex post-processing due to the unstructured output.

Text Spotting

LI-Net: Large-Pose Identity-Preserving Face Reenactment Network

no code implementations7 Apr 2021 Jin Liu, Peng Chen, Tao Liang, Zhaoxing Li, Cai Yu, Shuqiao Zou, Jiao Dai, Jizhong Han

Face reenactment is a challenging task, as it is difficult to maintain accurate expression, pose and identity simultaneously.

Face Reenactment

An efficient method for goal-oriented linear Bayesian optimal experimental design: Application to optimal sensor placemen

1 code implementation12 Feb 2021 Keyi Wu, Peng Chen, Omar Ghattas

Optimal experimental design (OED) plays an important role in the problem of identifying uncertainty with limited experimental data.

Optimization and Control Numerical Analysis Numerical Analysis

Projected Wasserstein gradient descent for high-dimensional Bayesian inference

1 code implementation12 Feb 2021 Yifei Wang, Peng Chen, Wuchen Li

We propose a projected Wasserstein gradient descent method (pWGD) for high-dimensional Bayesian inference problems.

Bayesian Inference Density Estimation +1

$SU(5)$ GUTs with $A_4$ modular symmetry

no code implementations29 Jan 2021 Peng Chen, Gui-Jun Ding, Stephen F. King

We combine $SU(5)$ Grand Unified Theories (GUTs) with $A_4$ modular symmetry and present a comprehensive analysis of the resulting quark and lepton mass matrices for all the simplest cases.

High Energy Physics - Phenomenology

Single-path Bit Sharing for Automatic Loss-aware Model Compression

no code implementations13 Jan 2021 Jing Liu, Bohan Zhuang, Peng Chen, Chunhua Shen, Jianfei Cai, Mingkui Tan

By jointly training the binary gates in conjunction with network parameters, the compression configurations of each layer can be automatically determined.

Model Compression Network Pruning +1

Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs

1 code implementation30 Nov 2020 Thomas O'Leary-Roseberry, Umberto Villa, Peng Chen, Omar Ghattas

We use the projection basis vectors in the active subspace as well as the principal output subspace to construct the weights for the first and last layers of the neural network, respectively.

Experimental Design Uncertainty Quantification

Fully Quantized Image Super-Resolution Networks

1 code implementation29 Nov 2020 Hu Wang, Peng Chen, Bohan Zhuang, Chunhua Shen

With the rising popularity of intelligent mobile devices, it is of great practical significance to develop accurate, realtime and energy-efficient image Super-Resolution (SR) inference methods.

Image Super-Resolution Quantization

FATNN: Fast and Accurate Ternary Neural Networks

no code implementations ICCV 2021 Peng Chen, Bohan Zhuang, Chunhua Shen

Ternary Neural Networks (TNNs) have received much attention due to being potentially orders of magnitude faster in inference, as well as more power efficient, than full-precision counterparts.

Image Classification Quantization

AQD: Towards Accurate Fully-Quantized Object Detection

1 code implementation CVPR 2021 Peng Chen, Jing Liu, Bohan Zhuang, Mingkui Tan, Chunhua Shen

Network quantization allows inference to be conducted using low-precision arithmetic for improved inference efficiency of deep neural networks on edge devices.

Image Classification Object +3

Deep Neural Network-Based Quantized Signal Reconstruction for DOA Estimation

no code implementations3 May 2020 Weifeng Han, Peng Chen, Zhenxin Cao

In this letter, a direction of angle (DOA) estimation problem is investigated with low-cost ADC in IRS, and we propose a deep neural network (DNN) as a recovery method for the low-resolution sampled signal.

Denoising Quantization

Predictions from warped flavordynamics based on the $T'$ family group

no code implementations5 Mar 2020 Peng Chen, Gui-Jun Ding, Jun-Nan Lu, José W. F. Valle

We propose a realistic theory of fermion masses and mixings using a five-dimensional warped scenario where all fermions propagate in the bulk and the Higgs field is localized on the IR brane.

High Energy Physics - Phenomenology

Tensor train construction from tensor actions, with application to compression of large high order derivative tensors

1 code implementation14 Feb 2020 Nick Alger, Peng Chen, Omar Ghattas

We present a method for converting tensors into tensor train format based on actions of the tensor as a vector-valued multilinear function.

Numerical Analysis Numerical Analysis

Projected Stein Variational Gradient Descent

1 code implementation NeurIPS 2020 Peng Chen, Omar Ghattas

The curse of dimensionality is a longstanding challenge in Bayesian inference in high dimensions.

Bayesian Inference

Training-free Monocular 3D Event Detection System for Traffic Surveillance

no code implementations1 Feb 2020 Lijun Yu, Peng Chen, Wenhe Liu, Guoliang Kang, Alexander G. Hauptmann

To deal with the aforementioned problems, in this paper, we propose a training-free monocular 3D event detection system for traffic surveillance.

Event Detection

Physics-Based Iterative Reconstruction for Dual Source and Flying Focal Spot Computed Tomography

no code implementations26 Jan 2020 Xiao Wang, Robert D. MacDougall, Peng Chen, Charles A. Bouman, Simon K. Warfield

Our algorithm uses precise physics models to reconstruct from the native cone-beam geometry and interleaved dual source helical trajectory of a DS-FFS CT. To do so, we construct a noise physics model to represent data acquisition noise and a prior image model to represent image noise and texture.

Computed Tomography (CT)

Audio-based automatic mating success prediction of giant pandas

no code implementations24 Dec 2019 WeiRan Yan, MaoLin Tang, Qijun Zhao, Peng Chen, Dunwu Qi, Rong Hou, Zhihe Zhang

Giant pandas, stereotyped as silent animals, make significantly more vocal sounds during breeding season, suggesting that sounds are essential for coordinating their reproduction and expression of mating preference.

One-Shot Imitation Filming of Human Motion Videos

no code implementations23 Dec 2019 Chong Huang, Yuanjie Dang, Peng Chen, Xin Yang, Kwang-Ting, Cheng

Imitation learning has been applied to mimic the operation of a human cameraman in several autonomous cinematography systems.

Imitation Learning Style Transfer

DLA: Dense-Layer-Analysis for Adversarial Example Detection

no code implementations5 Nov 2019 Philip Sperl, Ching-Yu Kao, Peng Chen, Konstantin Böttinger

In this paper, we present a novel end-to-end framework to detect such attacks during classification without influencing the target model's performance.

Autonomous Driving General Classification

A New Atomic Norm for DOA Estimation With Gain-Phase Errors

no code implementations5 Oct 2019 Peng Chen, Zhimin Chen, Zhenxin Cao, Xianbin Wang

The problem of direction of arrival (DOA) estimation has been studied for decades as an essential technology in enabling radar, wireless communications, and array signal processing related applications.

Structured Binary Neural Networks for Image Recognition

no code implementations22 Sep 2019 Bohan Zhuang, Chunhua Shen, Mingkui Tan, Peng Chen, Lingqiao Liu, Ian Reid

Experiments on both classification, semantic segmentation and object detection tasks demonstrate the superior performance of the proposed methods over various quantized networks in the literature.

object-detection Object Detection +2

Learning Deep Representations by Mutual Information for Person Re-identification

no code implementations16 Aug 2019 Peng Chen, Tong Jia, Pengfei Wu, Jianjun Wu, Dongyue Chen

Most existing person re-identification (ReID) methods have good feature representations to distinguish pedestrians with deep convolutional neural network (CNN) and metric learning methods.

Metric Learning Person Re-Identification

Distinguishing Individual Red Pandas from Their Faces

no code implementations9 Aug 2019 Qi He, Qijun Zhao, Ning Liu, Peng Chen, Zhihe Zhang, Rong Hou

We are going to release our database and model in the public domain to promote the research on automatic animal identification and particularly on the technique for protecting red pandas.

MAAM: A Morphology-Aware Alignment Model for Unsupervised Bilingual Lexicon Induction

no code implementations ACL 2019 Pengcheng Yang, Fuli Luo, Peng Chen, Tianyu Liu, Xu sun

The task of unsupervised bilingual lexicon induction (UBLI) aims to induce word translations from monolingual corpora in two languages.

Bilingual Lexicon Induction Denoising +2

Dense Procedure Captioning in Narrated Instructional Videos

no code implementations ACL 2019 Botian Shi, Lei Ji, Yaobo Liang, Nan Duan, Peng Chen, Zhendong Niu, Ming Zhou

Understanding narrated instructional videos is important for both research and real-world web applications.

Dense Captioning

Matryoshka: Fuzzing Deeply Nested Branches

no code implementations29 May 2019 Peng Chen, Jianzhong Liu, Hao Chen

Our evaluation also uncovered the key technique contributing to Matryoshka's impressive performance: it collects only the nesting constraints that may cause the target conditional statements unreachable, which greatly simplifies the constraints that it has to solve.

Cryptography and Security

Power Allocation in Multi-User Cellular Networks: Deep Reinforcement Learning Approaches

1 code implementation22 Jan 2019 Fan Meng, Peng Chen, Lenan Wu, Julian Cheng

The model-based power allocation algorithm has been investigated for decades, but it requires the mathematical models to be analytically tractable and it usually has high computational complexity.

Information Theory Information Theory

Power Allocation in Multi-user Cellular Networks With Deep Q Learning Approach

2 code implementations7 Dec 2018 Fan Meng, Peng Chen, Lenan Wu

Nowadays, the data-driven model-free machine learning-based approaches are rapidly developed in this field, and among them the deep reinforcement learning (DRL) is proved to be of great promising potential.

Information Theory Information Theory

Style Transfer as Unsupervised Machine Translation

no code implementations23 Aug 2018 Zhirui Zhang, Shuo Ren, Shujie Liu, Jianyong Wang, Peng Chen, Mu Li, Ming Zhou, Enhong Chen

Language style transferring rephrases text with specific stylistic attributes while preserving the original attribute-independent content.

Attribute NMT +4

Off-Grid DOA Estimation Using Sparse Bayesian Learning in MIMO Radar With Unknown Mutual Coupling

no code implementations12 Apr 2018 Peng Chen, Zhenxin Cao, Zhimin Chen, Xianbin Wang

With regard to the DOA estimation performance, the proposed SBLMC method can outperform state-of-the-art methods in the MIMO radar with unknown mutual coupling effect, while keeping the acceptable computational complexity.

Angora: Efficient Fuzzing by Principled Search

2 code implementations4 Mar 2018 Peng Chen, Hao Chen

On the LAVA-M data set, Angora found almost all the injected bugs, found more bugs than any other fuzzer that we compared with, and found eight times as many bugs as the second-best fuzzer in the program who.

Cryptography and Security

Question Generation for Question Answering

no code implementations EMNLP 2017 Nan Duan, Duyu Tang, Peng Chen, Ming Zhou

This paper presents how to generate questions from given passages using neural networks, where large scale QA pairs are automatically crawled and processed from Community-QA website, and used as training data.

Chatbot Question Answering +5

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