Search Results for author: XiaoFeng Wang

Found 45 papers, 11 papers with code

DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation

no code implementations11 Mar 2024 Guosheng Zhao, XiaoFeng Wang, Zheng Zhu, Xinze Chen, Guan Huang, Xiaoyi Bao, Xingang Wang

DriveDreamer-2 is the first world model to generate customized driving videos, it can generate uncommon driving videos (e. g., vehicles abruptly cut in) in a user-friendly manner.

Autonomous Driving Language Modelling +2

DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training

no code implementations5 Mar 2024 ZiHao Wang, Rui Zhu, Dongruo Zhou, Zhikun Zhang, John Mitchell, Haixu Tang, XiaoFeng Wang

DPAdapter modifies and enhances the sharpness-aware minimization (SAM) technique, utilizing a two-batch strategy to provide a more accurate perturbation estimate and an efficient gradient descent, thereby improving parameter robustness against noise.

WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens

no code implementations18 Jan 2024 XiaoFeng Wang, Zheng Zhu, Guan Huang, Boyuan Wang, Xinze Chen, Jiwen Lu

World models play a crucial role in understanding and predicting the dynamics of the world, which is essential for video generation.

Video Editing Video Generation

Malla: Demystifying Real-world Large Language Model Integrated Malicious Services

no code implementations6 Jan 2024 Zilong Lin, Jian Cui, Xiaojing Liao, XiaoFeng Wang

The underground exploitation of large language models (LLMs) for malicious services (i. e., Malla) is witnessing an uptick, amplifying the cyber threat landscape and posing questions about the trustworthiness of LLM technologies.

Language Modelling Large Language Model

Nighttime Person Re-Identification via Collaborative Enhancement Network with Multi-domain Learning

no code implementations25 Dec 2023 Andong Lu, Tianrui Zha, Chenglong Li, Jin Tang, XiaoFeng Wang, Bin Luo

To perform effective collaborative modeling between image relighting and person ReID tasks, we integrate the multilevel feature interactions in CENet.

Image Relighting Person Re-Identification

On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving

1 code implementation9 Nov 2023 Licheng Wen, Xuemeng Yang, Daocheng Fu, XiaoFeng Wang, Pinlong Cai, Xin Li, Tao Ma, Yingxuan Li, Linran Xu, Dengke Shang, Zheng Zhu, Shaoyan Sun, Yeqi Bai, Xinyu Cai, Min Dou, Shuanglu Hu, Botian Shi, Yu Qiao

This has been a significant bottleneck, particularly in the development of common sense reasoning and nuanced scene understanding necessary for safe and reliable autonomous driving.

Autonomous Driving Common Sense Reasoning +4

The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks

no code implementations24 Oct 2023 Xiaoyi Chen, Siyuan Tang, Rui Zhu, Shijun Yan, Lei Jin, ZiHao Wang, Liya Su, XiaoFeng Wang, Haixu Tang

In the attack, one can construct a PII association task, whereby an LLM is fine-tuned using a minuscule PII dataset, to potentially reinstate and reveal concealed PIIs.

Large Language Model Soft Ideologization via AI-Self-Consciousness

no code implementations28 Sep 2023 Xiaotian Zhou, Qian Wang, XiaoFeng Wang, Haixu Tang, Xiaozhong Liu

Large language models (LLMs) have demonstrated human-level performance on a vast spectrum of natural language tasks.

Language Modelling Large Language Model

Reliable Majority Vote Computation with Complementary Sequences for UAV Waypoint Flight Control

no code implementations26 Sep 2023 Alphan Sahin, XiaoFeng Wang

In this study, we propose a non-coherent over-the-air computation (OAC) scheme to calculate the majority vote (MV) reliably in fading channels.

DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving

no code implementations18 Sep 2023 XiaoFeng Wang, Zheng Zhu, Guan Huang, Xinze Chen, Jiagang Zhu, Jiwen Lu

The established world model holds immense potential for the generation of high-quality driving videos, and driving policies for safe maneuvering.

Autonomous Driving Video Generation

Towards Imbalanced Large Scale Multi-label Classification with Partially Annotated Labels

no code implementations31 Jul 2023 Xin Zhang, Yuqi Song, Fei Zuo, XiaoFeng Wang

In this work, we address the issue of label imbalance and investigate how to train classifiers using partial labels in large labeling spaces.

Multi-Label Classification

CDUL: CLIP-Driven Unsupervised Learning for Multi-Label Image Classification

no code implementations ICCV 2023 Rabab Abdelfattah, Qing Guo, Xiaoguang Li, XiaoFeng Wang, Song Wang

Using the aggregated similarity scores as the initial pseudo labels at the training stage, we propose an optimization framework to train the parameters of the classification network and refine pseudo labels for unobserved labels.

Classification Multi-Label Image Classification +2

Prompt Injection attack against LLM-integrated Applications

no code implementations8 Jun 2023 Yi Liu, Gelei Deng, Yuekang Li, Kailong Wang, ZiHao Wang, XiaoFeng Wang, Tianwei Zhang, Yepang Liu, Haoyu Wang, Yan Zheng, Yang Liu

We deploy HouYi on 36 actual LLM-integrated applications and discern 31 applications susceptible to prompt injection.

MAWSEO: Adversarial Wiki Search Poisoning for Illicit Online Promotion

no code implementations22 Apr 2023 Zilong Lin, Zhengyi Li, Xiaojing Liao, XiaoFeng Wang, Xiaozhong Liu

As a prominent instance of vandalism edits, Wiki search poisoning for illicit promotion is a cybercrime in which the adversary aims at editing Wiki articles to promote illicit businesses through Wiki search results of relevant queries.

D-Score: A White-Box Diagnosis Score for CNNs Based on Mutation Operators

no code implementations3 Apr 2023 Xin Zhang, Yuqi Song, XiaoFeng Wang, Fei Zuo

However, concerns have been raised with respect to the trustworthiness of these models: The standard testing method evaluates the performance of a model on a test set, while low-quality and insufficient test sets can lead to unreliable evaluation results, which can have unforeseeable consequences.

Autonomous Driving Data Augmentation +1

SSL-Cleanse: Trojan Detection and Mitigation in Self-Supervised Learning

no code implementations16 Mar 2023 Mengxin Zheng, Jiaqi Xue, ZiHao Wang, Xun Chen, Qian Lou, Lei Jiang, XiaoFeng Wang

We evaluated SSL-Cleanse on various datasets using 1200 encoders, achieving an average detection success rate of 82. 2% on ImageNet-100.

Self-Supervised Learning

OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception

1 code implementation ICCV 2023 XiaoFeng Wang, Zheng Zhu, Wenbo Xu, Yunpeng Zhang, Yi Wei, Xu Chi, Yun Ye, Dalong Du, Jiwen Lu, Xingang Wang

Towards a comprehensive benchmarking of surrounding perception algorithms, we propose OpenOccupancy, which is the first surrounding semantic occupancy perception benchmark.

Autonomous Driving Benchmarking

CSDR-BERT: a pre-trained scientific dataset match model for Chinese Scientific Dataset Retrieval

no code implementations30 Jan 2023 Xintao Chu, Jianping Liu, Jian Wang, XiaoFeng Wang, Yingfei Wang, Meng Wang, Xunxun Gu

As the number of open and shared scientific datasets on the Internet increases under the open science movement, efficiently retrieving these datasets is a crucial task in information retrieval (IR) research.

Information Retrieval Retrieval +2

Gradient Shaping: Enhancing Backdoor Attack Against Reverse Engineering

no code implementations29 Jan 2023 Rui Zhu, Di Tang, Siyuan Tang, Guanhong Tao, Shiqing Ma, XiaoFeng Wang, Haixu Tang

Finally, we perform both theoretical and experimental analysis, showing that the GRASP enhancement does not reduce the effectiveness of the stealthy attacks against the backdoor detection methods based on weight analysis, as well as other backdoor mitigation methods without using detection.

Backdoor Attack

FE-TCM: Filter-Enhanced Transformer Click Model for Web Search

no code implementations19 Jan 2023 Yingfei Wang, Jianping Liu, Jian Wang, XiaoFeng Wang, Meng Wang, Xintao Chu

In this paper, We use Transformer as the backbone network of feature extraction, add filter layer innovatively, and propose a new Filter-Enhanced Transformer Click Model (FE-TCM) for web search.

Are We Ready for Vision-Centric Driving Streaming Perception? The ASAP Benchmark

1 code implementation CVPR 2023 XiaoFeng Wang, Zheng Zhu, Yunpeng Zhang, Guan Huang, Yun Ye, Wenbo Xu, Ziwei Chen, Xingang Wang

To mitigate the problem, we propose the Autonomous-driving StreAming Perception (ASAP) benchmark, which is the first benchmark to evaluate the online performance of vision-centric perception in autonomous driving.

Depth Estimation Motion Forecasting

Selective Amnesia: On Efficient, High-Fidelity and Blind Suppression of Backdoor Effects in Trojaned Machine Learning Models

no code implementations9 Dec 2022 Rui Zhu, Di Tang, Siyuan Tang, XiaoFeng Wang, Haixu Tang

Our idea is to retrain a given DNN model on randomly labeled clean data, to induce a CF on the model, leading to a sudden forget on both primary and backdoor tasks; then we recover the primary task by retraining the randomized model on correctly labeled clean data.

Continual Learning

An Effective Approach for Multi-label Classification with Missing Labels

no code implementations24 Oct 2022 Xin Zhang, Rabab Abdelfattah, Yuqi Song, XiaoFeng Wang

Through comprehensive experiments on three large-scale multi-label image datasets, i. e. MS-COCO, NUS-WIDE, and Pascal VOC12, we show that our method can handle the imbalance between positive labels and negative labels, while still outperforming existing missing-label learning approaches in most cases, and in some cases even approaches with fully labeled datasets.

Classification Missing Labels +2

Depth Monocular Estimation with Attention-based Encoder-Decoder Network from Single Image

no code implementations24 Oct 2022 Xin Zhang, Rabab Abdelfattah, Yuqi Song, Samuel A. Dauchert, XiaoFeng Wang

Depth information is the foundation of perception, essential for autonomous driving, robotics, and other source-constrained applications.

Autonomous Driving SSIM

G2NetPL: Generic Game-Theoretic Network for Partial-Label Image Classification

no code implementations20 Oct 2022 Rabab Abdelfattah, Xin Zhang, Mostafa M. Fouda, XiaoFeng Wang, Song Wang

To effectively address partial-label classification, this paper proposes an end-to-end Generic Game-theoretic Network (G2NetPL) for partial-label learning, which can be applied to most partial-label settings, including a very challenging, but annotation-efficient case where only a subset of the training images are labeled, each with only one positive label, while the rest of the training images remain unlabeled.

Multi-Label Classification Multi-Label Image Classification +2

Understanding Impacts of Task Similarity on Backdoor Attack and Detection

no code implementations12 Oct 2022 Di Tang, Rui Zhu, XiaoFeng Wang, Haixu Tang, Yi Chen

With extensive studies on backdoor attack and detection, still fundamental questions are left unanswered regarding the limits in the adversary's capability to attack and the defender's capability to detect.

Backdoor Attack Multi-Task Learning

Scenario-Adaptive and Self-Supervised Model for Multi-Scenario Personalized Recommendation

no code implementations24 Aug 2022 Yuanliang Zhang, XiaoFeng Wang, Jinxin Hu, Ke Gao, Chenyi Lei, Fei Fang

we summarize three practical challenges which are not well solved for multi-scenario modeling: (1) Lacking of fine-grained and decoupled information transfer controls among multiple scenarios.

Contrastive Learning Disentanglement +1

Crafting Monocular Cues and Velocity Guidance for Self-Supervised Multi-Frame Depth Learning

1 code implementation19 Aug 2022 XiaoFeng Wang, Zheng Zhu, Guan Huang, Xu Chi, Yun Ye, Ziwei Chen, Xingang Wang

In contrast, multi-frame depth estimation methods improve the depth accuracy thanks to the success of Multi-View Stereo (MVS), which directly makes use of geometric constraints.

Depth Estimation

MVSTER: Epipolar Transformer for Efficient Multi-View Stereo

1 code implementation15 Apr 2022 XiaoFeng Wang, Zheng Zhu, Fangbo Qin, Yun Ye, Guan Huang, Xu Chi, Yijia He, Xingang Wang

Therefore, we present MVSTER, which leverages the proposed epipolar Transformer to learn both 2D semantics and 3D spatial associations efficiently.

New Benchmark for Household Garbage Image Recognition

no code implementations24 Feb 2022 Zhize Wu, Huanyi Li, XiaoFeng Wang, Zijun Wu, Le Zou, Lixiang Xu, Ming Tan

Household garbage images are usually faced with complex backgrounds, variable illuminations, diverse angles, and changeable shapes, which bring a great difficulty in garbage image classification.

Classification Image Classification +1

Context-aware Heterogeneous Graph Attention Network for User Behavior Prediction in Local Consumer Service Platform

no code implementations24 Jun 2021 Peiyuan Zhu, XiaoFeng Wang, Zisen Sang, Aiquan Yuan, Guodong Cao

Hence, in this paper, we propose a context-aware heterogeneous graph attention network (CHGAT) to dynamically generate the representation of the user and to estimate the probability for future behavior.

Graph Attention

SoK: A Modularized Approach to Study the Security of Automatic Speech Recognition Systems

1 code implementation19 Mar 2021 Yuxuan Chen, Jiangshan Zhang, Xuejing Yuan, Shengzhi Zhang, Kai Chen, XiaoFeng Wang, Shanqing Guo

In this paper, we present our systematization of knowledge for ASR security and provide a comprehensive taxonomy for existing work based on a modularized workflow.

Adversarial Attack Automatic Speech Recognition +3

The effect of aspherical stellar wind of giant stars on the symbiotic channel of type Ia supernovae

no code implementations18 Feb 2021 Chengyuan Wu, Dongdong Liu, XiaoFeng Wang, Bo wang

The progenitor systems accounting for explosions of type Ia supernovae (SNe Ia) is still under debate.

Solar and Stellar Astrophysics

HyMap: eliciting hypotheses in early-stage software startups using cognitive mapping

no code implementations18 Feb 2021 Jorge Melegati, Eduardo Guerra, XiaoFeng Wang

Regarding the first, it provides a better understanding of the guidance founders use to develop their startups and, for the latter, a technique to identify hypotheses in early-stage software startups.

Computers and Society

Towards Dark Jargon Interpretation in Underground Forums

no code implementations5 Nov 2020 Dominic Seyler, Wei Liu, XiaoFeng Wang, ChengXiang Zhai

Dark jargons are benign-looking words that have hidden, sinister meanings and are used by participants of underground forums for illicit behavior.

TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines

1 code implementation20 Oct 2020 Rabab Abdelfattah, XiaoFeng Wang, Song Wang

Accurate detection and segmentation of transmission towers~(TTs) and power lines~(PLs) from aerial images plays a key role in protecting power-grid security and low-altitude UAV safety.

Instance Segmentation object-detection +3

Query-Free Attacks on Industry-Grade Face Recognition Systems under Resource Constraints

no code implementations13 Feb 2018 Di Tang, XiaoFeng Wang, Kehuan Zhang

To launch black-box attacks against a Deep Neural Network (DNN) based Face Recognition (FR) system, one needs to build \textit{substitute} models to simulate the target model, so the adversarial examples discovered from substitute models could also mislead the target model.

Face Recognition

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