Search Results for author: Qiang Xu

Found 62 papers, 25 papers with code

MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenes

no code implementations23 May 2024 Ruiyuan Gao, Kai Chen, Zhihao LI, Lanqing Hong, Zhenguo Li, Qiang Xu

While controllable generative models for images and videos have achieved remarkable success, high-quality models for 3D scenes, particularly in unbounded scenarios like autonomous driving, remain underdeveloped due to high data acquisition costs.

3D Generation Autonomous Driving +2

BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion

2 code implementations11 Mar 2024 Xuan Ju, Xian Liu, Xintao Wang, Yuxuan Bian, Ying Shan, Qiang Xu

Image inpainting, the process of restoring corrupted images, has seen significant advancements with the advent of diffusion models (DMs).

Image Inpainting

Evaluating Text-to-Image Generative Models: An Empirical Study on Human Image Synthesis

no code implementations8 Mar 2024 Muxi Chen, Yi Liu, Jian Yi, Changran Xu, Qiuxia Lai, Hongliang Wang, Tsung-Yi Ho, Qiang Xu

In this paper, we present an empirical study introducing a nuanced evaluation framework for text-to-image (T2I) generative models, applied to human image synthesis.

Defect Detection Fairness +1

GuardT2I: Defending Text-to-Image Models from Adversarial Prompts

no code implementations3 Mar 2024 Yijun Yang, Ruiyuan Gao, Xiao Yang, Jianyuan Zhong, Qiang Xu

Recent advancements in Text-to-Image (T2I) models have raised significant safety concerns about their potential misuse for generating inappropriate or Not-Safe-For-Work (NSFW) contents, despite existing countermeasures such as NSFW classifiers or model fine-tuning for inappropriate concept removal.

Binary Classification Language Modelling +1

Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning

no code implementations7 Feb 2024 Yuxuan Bian, Xuan Ju, Jiangtong Li, Zhijian Xu, Dawei Cheng, Qiang Xu

In this study, we present aLLM4TS, an innovative framework that adapts Large Language Models (LLMs) for time-series representation learning.

Contrastive Learning Representation Learning +3

Text Image Inpainting via Global Structure-Guided Diffusion Models

1 code implementation26 Jan 2024 Shipeng Zhu, Pengfei Fang, Chenjie Zhu, Zuoyan Zhao, Qiang Xu, Hui Xue

Leveraging the global structure of the text as a prior, the proposed GSDM develops an efficient diffusion model to recover clean texts.

Image Inpainting Scene Text Recognition

LLM4EDA: Emerging Progress in Large Language Models for Electronic Design Automation

1 code implementation28 Dec 2023 RuiZhe Zhong, Xingbo Du, Shixiong Kai, Zhentao Tang, Siyuan Xu, Hui-Ling Zhen, Jianye Hao, Qiang Xu, Mingxuan Yuan, Junchi Yan

Since circuit can be represented with HDL in a textual format, it is reasonable to question whether LLMs can be leveraged in the EDA field to achieve fully automated chip design and generate circuits with improved power, performance, and area (PPA).

Answer Generation Chatbot

Non-Cross Diffusion for Semantic Consistency

no code implementations30 Nov 2023 Ziyang Zheng, Ruiyuan Gao, Qiang Xu

In diffusion models, deviations from a straight generative flow are a common issue, resulting in semantic inconsistencies and suboptimal generations.

MMA-Diffusion: MultiModal Attack on Diffusion Models

2 code implementations29 Nov 2023 Yijun Yang, Ruiyuan Gao, Xiaosen Wang, Tsung-Yi Ho, Nan Xu, Qiang Xu

In recent years, Text-to-Image (T2I) models have seen remarkable advancements, gaining widespread adoption.

Direct Inversion: Boosting Diffusion-based Editing with 3 Lines of Code

1 code implementation2 Oct 2023 Xuan Ju, Ailing Zeng, Yuxuan Bian, Shaoteng Liu, Qiang Xu

Specifically, in the context of diffusion-based editing, where a source image is edited according to a target prompt, the process commences by acquiring a noisy latent vector corresponding to the source image via the diffusion model.

Image Generation Text-based Image Editing

DiffGuard: Semantic Mismatch-Guided Out-of-Distribution Detection using Pre-trained Diffusion Models

1 code implementation ICCV 2023 Ruiyuan Gao, Chenchen Zhao, Lanqing Hong, Qiang Xu

There is a recent work that directly applies it to OOD detection, which employs a conditional Generative Adversarial Network (cGAN) to enlarge semantic mismatch in the image space.

Generative Adversarial Network Out-of-Distribution Detection

FITS: Modeling Time Series with $10k$ Parameters

1 code implementation6 Jul 2023 Zhijian Xu, Ailing Zeng, Qiang Xu

In this paper, we introduce FITS, a lightweight yet powerful model for time series analysis.

Anomaly Detection Time Series +1

DeepGate2: Functionality-Aware Circuit Representation Learning

1 code implementation25 May 2023 Zhengyuan Shi, Hongyang Pan, Sadaf Khan, Min Li, Yi Liu, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Zhufei Chu, Qiang Xu

Circuit representation learning aims to obtain neural representations of circuit elements and has emerged as a promising research direction that can be applied to various EDA and logic reasoning tasks.

Representation Learning

HumanSD: A Native Skeleton-Guided Diffusion Model for Human Image Generation

1 code implementation ICCV 2023 Xuan Ju, Ailing Zeng, Chenchen Zhao, Jianan Wang, Lei Zhang, Qiang Xu

While such a plug-and-play approach is appealing, the inevitable and uncertain conflicts between the original images produced from the frozen SD branch and the given condition incur significant challenges for the learnable branch, which essentially conducts image feature editing for condition enforcement.

Denoising Image Generation

Pi-ViMo: Physiology-inspired Robust Vital Sign Monitoring using mmWave Radars

no code implementations24 Mar 2023 Bo Zhang, Boyu Jiang, Rong Zheng, XiaoPing Zhang, Jun Li, Qiang Xu

In this paper, we address these limitations and present "Pi-ViMo", a non-contact Physiology-inspired Robust Vital Sign Monitoring system, using mmWave radars.

Template Matching

Active Teacher for Semi-Supervised Object Detection

1 code implementation CVPR 2022 Peng Mi, Jianghang Lin, Yiyi Zhou, Yunhang Shen, Gen Luo, Xiaoshuai Sun, Liujuan Cao, Rongrong Fu, Qiang Xu, Rongrong Ji

In this paper, we study teacher-student learning from the perspective of data initialization and propose a novel algorithm called Active Teacher(Source code are available at: \url{https://github. com/HunterJ-Lin/ActiveTeacher}) for semi-supervised object detection (SSOD).

Object object-detection +2

DeepSeq: Deep Sequential Circuit Learning

no code implementations27 Feb 2023 Sadaf Khan, Zhengyuan Shi, Min Li, Qiang Xu

Circuit representation learning is a promising research direction in the electronic design automation (EDA) field.

Representation Learning

FrAug: Frequency Domain Augmentation for Time Series Forecasting

no code implementations18 Feb 2023 Muxi Chen, Zhijian Xu, Ailing Zeng, Qiang Xu

In time series forecasting (TSF), we need to model the fine-grained temporal relationship within time series segments to generate accurate forecasting results given data in a look-back window.

Anomaly Detection Data Augmentation +3

On Function-Coupled Watermarks for Deep Neural Networks

no code implementations8 Feb 2023 Xiangyu Wen, Yu Li, Wei Jiang, Qiang Xu

Various watermarking techniques are proposed to protect such intellectual properties (IPs), wherein the DNN providers implant secret information into the model so that they can later claim IP ownership by retrieving their embedded watermarks with some dedicated trigger inputs.

Image Classification

An Empirical Study on the Efficacy of Deep Active Learning for Image Classification

no code implementations30 Nov 2022 Yu Li, Muxi Chen, Yannan Liu, Daojing He, Qiang Xu

Third, performing data selection in the SSAL setting can achieve a significant and consistent performance improvement, especially with abundant unlabeled data.

Active Learning Image Classification

Joint Learning of Deep Texture and High-Frequency Features for Computer-Generated Image Detection

1 code implementation7 Sep 2022 Qiang Xu, Shan Jia, Xinghao Jiang, Tanfeng Sun, Zhe Wang, Hong Yan

Based on the finding that multiple different modules in image acquisition will lead to different sensitivity inconsistencies to the convolutional neural network (CNN)-based rendering in images, we propose a deep texture rendering module for texture difference enhancement and discriminative texture representation.

Generative Adversarial Network Semantic Segmentation

SATformer: Transformer-Based UNSAT Core Learning

no code implementations2 Sep 2022 Zhengyuan Shi, Min Li, Yi Liu, Sadaf Khan, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Qiang Xu

This paper introduces SATformer, a novel Transformer-based approach for the Boolean Satisfiability (SAT) problem.

Multi-Task Learning

Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning

no code implementations31 Aug 2022 Zhiyuan He, Yijun Yang, Pin-Yu Chen, Qiang Xu, Tsung-Yi Ho

Empowered by the robust relation net built on SSL, we found that BEYOND outperforms baselines in terms of both detection ability and speed.

Relation Self-Supervised Learning

Out-of-Distribution Detection with Semantic Mismatch under Masking

1 code implementation31 Jul 2022 Yijun Yang, Ruiyuan Gao, Qiang Xu

This paper proposes a novel out-of-distribution (OOD) detection framework named MoodCat for image classifiers.

Out-of-Distribution Detection Out of Distribution (OOD) Detection

DeepTPI: Test Point Insertion with Deep Reinforcement Learning

1 code implementation7 Jun 2022 Zhengyuan Shi, Min Li, Sadaf Khan, Liuzheng Wang, Naixing Wang, Yu Huang, Qiang Xu

Unlike previous learning-based solutions that formulate the TPI task as a supervised-learning problem, we train a novel DRL agent, instantiated as the combination of a graph neural network (GNN) and a Deep Q-Learning network (DQN), to maximize the test coverage improvement.

Q-Learning reinforcement-learning +1

DeepSAT: An EDA-Driven Learning Framework for SAT

no code implementations27 May 2022 Min Li, Zhengyuan Shi, Qiuxia Lai, Sadaf Khan, Shaowei Cai, Qiang Xu

Based on this observation, we approximate the SAT solving procedure with a conditional generative model, leveraging a novel directed acyclic graph neural network (DAGNN) with two polarity prototypes for conditional SAT modeling.

Are Transformers Effective for Time Series Forecasting?

4 code implementations26 May 2022 Ailing Zeng, Muxi Chen, Lei Zhang, Qiang Xu

Recently, there has been a surge of Transformer-based solutions for the long-term time series forecasting (LTSF) task.

Anomaly Detection Temporal Relation Extraction +2

DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation

1 code implementation16 Mar 2022 Ailing Zeng, Xuan Ju, Lei Yang, Ruiyuan Gao, Xizhou Zhu, Bo Dai, Qiang Xu

This paper proposes a simple baseline framework for video-based 2D/3D human pose estimation that can achieve 10 times efficiency improvement over existing works without any performance degradation, named DeciWatch.

2D Human Pose Estimation 3D Human Pose Estimation +2

SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos

2 code implementations27 Dec 2021 Ailing Zeng, Lei Yang, Xuan Ju, Jiefeng Li, Jianyi Wang, Qiang Xu

With a simple yet effective motion-aware fully-connected network, SmoothNet improves the temporal smoothness of existing pose estimators significantly and enhances the estimation accuracy of those challenging frames as a side-effect.

2D Human Pose Estimation 3D Human Pose Estimation +2

DeepFIB: Self-Imputation for Time Series Anomaly Detection

no code implementations12 Dec 2021 Minhao Liu, Zhijian Xu, Qiang Xu

Due to the inherently unpredictable and highly varied nature of anomalies and the lack of anomaly labels in historical data, the AD problem is typically formulated as an unsupervised learning problem.

Anomaly Detection Fraud Detection +4

Testability-Aware Low Power Controller Design with Evolutionary Learning

1 code implementation26 Nov 2021 Min Li, Zhengyuan Shi, Zezhong Wang, Weiwei Zhang, Yu Huang, Qiang Xu

The proposed GA-guided XORNets also allows reducing the number of control bits, and the total testing time decreases by 20. 78% on average and up to 47. 09% compared to the existing design without sacrificing test coverage.

DeepGate: Learning Neural Representations of Logic Gates

1 code implementation26 Nov 2021 Min Li, Sadaf Khan, Zhengyuan Shi, Naixing Wang, Yu Huang, Qiang Xu

We propose DeepGate, a novel representation learning solution that effectively embeds both logic function and structural information of a circuit as vectors on each gate.

Representation Learning

T-WaveNet: A Tree-Structured Wavelet Neural Network for Time Series Signal Analysis

no code implementations ICLR 2022 Minhao Liu, Ailing Zeng, Qiuxia Lai, Ruiyuan Gao, Min Li, Jing Qin, Qiang Xu

In this work, we propose a novel tree-structured wavelet neural network for time series signal analysis, namely T-WaveNet, by taking advantage of an inherent property of various types of signals, known as the dominant frequency range.

Activity Recognition Representation Learning +3

Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation

no code implementations ICCV 2021 Ailing Zeng, Xiao Sun, Lei Yang, Nanxuan Zhao, Minhao Liu, Qiang Xu

While the average prediction accuracy has been improved significantly over the years, the performance on hard poses with depth ambiguity, self-occlusion, and complex or rare poses is still far from satisfactory.

3D Human Pose Estimation 3D Pose Estimation +3

Information Bottleneck Approach to Spatial Attention Learning

1 code implementation7 Aug 2021 Qiuxia Lai, Yu Li, Ailing Zeng, Minhao Liu, Hanqiu Sun, Qiang Xu

Extensive experiments show that the proposed IB-inspired spatial attention mechanism can yield attention maps that neatly highlight the regions of interest while suppressing backgrounds, and bootstrap standard DNN structures for visual recognition tasks (e. g., image classification, fine-grained recognition, cross-domain classification).

Decision Making domain classification +1

SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction

4 code implementations17 Jun 2021 Minhao Liu, Ailing Zeng, Muxi Chen, Zhijian Xu, Qiuxia Lai, Lingna Ma, Qiang Xu

One unique property of time series is that the temporal relations are largely preserved after downsampling into two sub-sequences.

 Ranked #1 on Time Series Forecasting on ETTh1 (24) Multivariate (using extra training data)

Time Series Traffic Prediction +1

Relational Graph Neural Network Design via Progressive Neural Architecture Search

no code implementations30 May 2021 Ailing Zeng, Minhao Liu, Zhiwei Liu, Ruiyuan Gao, Jing Qin, Qiang Xu

We propose a novel solution to addressing a long-standing dilemma in the representation learning of graph neural networks (GNNs): how to effectively capture and represent useful information embedded in long-distance nodes to improve the performance of nodes with low homophily without leading to performance degradation in nodes with high homophily.

Neural Architecture Search Node Classification +1

TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks

no code implementations NeurIPS 2021 Yu Li, Min Li, Qiuxia Lai, Yannan Liu, Qiang Xu

To be specific, we first build a similarity graph on test instances and training samples, and we conduct graph-based semi-supervised learning to extract contextual features.

Image Classification

AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference

no code implementations10 May 2021 Min Li, Yu Li, Ye Tian, Li Jiang, Qiang Xu

This paper presents AppealNet, a novel edge/cloud collaborative architecture that runs deep learning (DL) tasks more efficiently than state-of-the-art solutions.

Image Classification

Skimming and Scanning for Untrimmed Video Action Recognition

no code implementations21 Apr 2021 Yunyan Hong, Ailing Zeng, Min Li, Cewu Lu, Li Jiang, Qiang Xu

Video action recognition (VAR) is a primary task of video understanding, and untrimmed videos are more common in real-life scenes.

Action Recognition Temporal Action Localization +1

T-WaveNet: Tree-Structured Wavelet Neural Network for Sensor-Based Time Series Analysis

no code implementations10 Dec 2020 Minhao Liu, Ailing Zeng, Qiuxia Lai, Qiang Xu

Motivated by the fact that usually a small subset of the frequency components carries the primary information for sensor data, we propose a novel tree-structured wavelet neural network for sensor data analysis, namely \emph{T-WaveNet}.

Activity Recognition Brain Computer Interface +5

DeepDyve: Dynamic Verification for Deep Neural Networks

no code implementations21 Sep 2020 Yu Li, Min Li, Bo Luo, Ye Tian, Qiang Xu

The key to enabling such lightweight checking is that the smaller neural network only needs to produce approximate results for the initial task without sacrificing fault coverage much.

Autonomous Driving

SRNet: Improving Generalization in 3D Human Pose Estimation with a Split-and-Recombine Approach

1 code implementation ECCV 2020 Ailing Zeng, Xiao Sun, Fuyang Huang, Minhao Liu, Qiang Xu, Stephen Lin

With the reduced dimensionality of less relevant body areas, the training set distribution within network branches more closely reflects the statistics of local poses instead of global body poses, without sacrificing information important for joint inference.

Monocular 3D Human Pose Estimation

The Effect of the Multi-Layer Text Summarization Model on the Efficiency and Relevancy of the Vector Space-based Information Retrieval

no code implementations18 Apr 2020 Ahmad Hussein Ababneh, Joan Lu, Qiang Xu

The purpose of this research is to measure the effect of the Multi-Layer Similarity model of the automatic text summarization on building an informative and condensed invert index in the IR systems.

Information Retrieval Retrieval +1

ICSTrace: A Malicious IP Traceback Model for Attacking Data of Industrial Control System

no code implementations30 Dec 2019 Feng Xiao, Qiang Xu

Considering the attacks against industrial control system are mostly organized and premeditated actions, IP traceback is significant for the security of industrial control system.

Clustering

DeepFuse: An IMU-Aware Network for Real-Time 3D Human Pose Estimation from Multi-View Image

no code implementations9 Dec 2019 Fuyang Huang, Ailing Zeng, Minhao Liu, Qiuxia Lai, Qiang Xu

In this paper, we propose a two-stage fully 3D network, namely \textbf{DeepFuse}, to estimate human pose in 3D space by fusing body-worn Inertial Measurement Unit (IMU) data and multi-view images deeply.

3D Human Pose Estimation 3D Pose Estimation

Region-Wise Attack: On Efficient Generation of Robust Physical Adversarial Examples

no code implementations5 Dec 2019 Bo Luo, Qiang Xu

Deep neural networks (DNNs) are shown to be susceptible to adversarial example attacks.

Adversarial Attack

On Functional Test Generation for Deep Neural Network IPs

no code implementations23 Nov 2019 Bo Luo, Yu Li, Lingxiao Wei, Qiang Xu

Considering the large amount of training data and know-how required to generate the network, it is more practical to use third-party DNN intellectual property (IP) cores for many designs.

Structure-Aware 3D Hourglass Network for Hand Pose Estimation from Single Depth Image

no code implementations26 Dec 2018 Fuyang Huang, Ailing Zeng, Minhao Liu, Jing Qin, Qiang Xu

Experimental results show that the proposed structure-aware 3D hourglass network is able to achieve a mean joint error of 7. 4 mm in MSRA and 8. 9 mm in NYU datasets, respectively.

Hand Pose Estimation

On Configurable Defense against Adversarial Example Attacks

no code implementations6 Dec 2018 Bo Luo, Min Li, Yu Li, Qiang Xu

Machine learning systems based on deep neural networks (DNNs) have gained mainstream adoption in many applications.

Invocation-driven Neural Approximate Computing with a Multiclass-Classifier and Multiple Approximators

1 code implementation19 Oct 2018 Haiyue Song, Chengwen Xu, Qiang Xu, Zhuoran Song, Naifeng Jing, Xiaoyao Liang, Li Jiang

We thus propose a novel approximate computing architecture with a Multiclass-Classifier and Multiple Approximators (MCMA).

I Know What You See: Power Side-Channel Attack on Convolutional Neural Network Accelerators

no code implementations5 Mar 2018 Lingxiao Wei, Bo Luo, Yu Li, Yannan Liu, Qiang Xu

Deep learning has become the de-facto computational paradigm for various kinds of perception problems, including many privacy-sensitive applications such as online medical image analysis.

Towards Imperceptible and Robust Adversarial Example Attacks against Neural Networks

no code implementations15 Jan 2018 Bo Luo, Yannan Liu, Lingxiao Wei, Qiang Xu

Previous adversarial example crafting methods, however, use simple metrics to evaluate the distances between the original examples and the adversarial ones, which could be easily detected by human eyes.

Cannot find the paper you are looking for? You can Submit a new open access paper.