Search Results for author: Yingying Chen

Found 25 papers, 8 papers with code

Occlusion-Aware Siamese Network for Human Pose Estimation

no code implementations ECCV 2020 Lu Zhou, Yingying Chen, Yunze Gao, Jinqiao Wang, Hanqing Lu

To overcome the defects caused by the erasing operation, we perform feature reconstruction to recover the information destroyed by occlusion and details lost in cleaning procedure.

Pose Estimation

Blended Grammar Network for Human Parsing

no code implementations ECCV 2020 Xiaomei Zhang, Yingying Chen, Bingke Zhu, Jinqiao Wang, Ming Tang

Although human parsing has made great progress, it still faces a challenge, i. e., how to extract the whole foreground from similar or cluttered scenes effectively.

Human Parsing

FiLo: Zero-Shot Anomaly Detection by Fine-Grained Description and High-Quality Localization

no code implementations21 Apr 2024 Zhaopeng Gu, Bingke Zhu, Guibo Zhu, Yingying Chen, Hao Li, Ming Tang, Jinqiao Wang

Zero-shot anomaly detection (ZSAD) methods entail detecting anomalies directly without access to any known normal or abnormal samples within the target item categories.

Anomaly Detection Position +1

Optimization of Prompt Learning via Multi-Knowledge Representation for Vision-Language Models

1 code implementation16 Apr 2024 Enming Zhang, Bingke Zhu, Yingying Chen, Qinghai Miao, Ming Tang, Jinqiao Wang

This limitation restricts the capabilities of pretrained VLMs and can result in incorrect predictions in downstream tasks.

DisDet: Exploring Detectability of Backdoor Attack on Diffusion Models

no code implementations5 Feb 2024 Yang Sui, Huy Phan, Jinqi Xiao, Tianfang Zhang, Zijie Tang, Cong Shi, Yan Wang, Yingying Chen, Bo Yuan

In this paper, for the first time, we systematically explore the detectability of the poisoned noise input for the backdoored diffusion models, an important performance metric yet little explored in the existing works.

Backdoor Attack

Adaptive Quantization for Key Generation in Low-Power Wide-Area Networks

no code implementations11 Oct 2023 Chen Chen, Junqing Zhang, Yingying Chen

Physical layer key generation based on reciprocal and random wireless channels has been an attractive solution for securing resource-constrained low-power wide-area networks (LPWANs).


AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Models

1 code implementation29 Aug 2023 Zhaopeng Gu, Bingke Zhu, Guibo Zhu, Yingying Chen, Ming Tang, Jinqiao Wang

Large Vision-Language Models (LVLMs) such as MiniGPT-4 and LLaVA have demonstrated the capability of understanding images and achieved remarkable performance in various visual tasks.

Anomaly Detection In-Context Learning

Benchmarking and Analyzing Robust Point Cloud Recognition: Bag of Tricks for Defending Adversarial Examples

1 code implementation ICCV 2023 Qiufan Ji, Lin Wang, Cong Shi, Shengshan Hu, Yingying Chen, Lichao Sun

In this paper, we first establish a comprehensive, and rigorous point cloud adversarial robustness benchmark to evaluate adversarial robustness, which can provide a detailed understanding of the effects of the defense and attack methods.

Adversarial Robustness Benchmarking

Privacy-Utility Balanced Voice De-Identification Using Adversarial Examples

no code implementations10 Nov 2022 Meng Chen, Li Lu, Jiadi Yu, Yingying Chen, Zhongjie Ba, Feng Lin, Kui Ren

In this paper, we propose a voice de-identification system, which uses adversarial examples to balance the privacy and utility of voice services.

De-identification Speaker Identification

View-Disentangled Transformer for Brain Lesion Detection

1 code implementation20 Sep 2022 Haofeng Li, Junjia Huang, Guanbin Li, Zhou Liu, Yihong Zhong, Yingying Chen, Yunfei Wang, Xiang Wan

Deep neural networks (DNNs) have been widely adopted in brain lesion detection and segmentation.

Lesion Detection

UniVIP: A Unified Framework for Self-Supervised Visual Pre-training

no code implementations CVPR 2022 Zhaowen Li, Yousong Zhu, Fan Yang, Wei Li, Chaoyang Zhao, Yingying Chen, Zhiyang Chen, Jiahao Xie, Liwei Wu, Rui Zhao, Ming Tang, Jinqiao Wang

Furthermore, our method can also exploit single-centric-object dataset such as ImageNet and outperforms BYOL by 2. 5% with the same pre-training epochs in linear probing, and surpass current self-supervised object detection methods on COCO dataset, demonstrating its universality and potential.

Image Classification Object +4

FewSense, Towards a Scalable and Cross-Domain Wi-Fi Sensing System Using Few-Shot Learning

no code implementations3 Mar 2022 Guolin Yin, Junqing Zhang, Guanxiong Shen, Yingying Chen

When the system was applied in the target domain, few samples were used to fine-tune the feature extractor for domain adaptation.

Domain Adaptation Few-Shot Learning

Simultaneous Monitoring of Multiple People's Vital Sign Leveraging a Single Phased-MIMO Radar

no code implementations15 Oct 2021 Zhaoyi Xu, Cong Shi, Tianfang Zhang, ShuPing Li, Yichao Yuan, Chung-Tse Michael Wu, Yingying Chen, Athina Petropulu

Based on the designed TDM phased-MIMO radar, we develop a system to automatically localize multiple human subjects and estimate their vital signs.

Improving Multiple Object Tracking With Single Object Tracking

no code implementations CVPR 2021 Linyu Zheng, Ming Tang, Yingying Chen, Guibo Zhu, Jinqiao Wang, Hanqing Lu

Despite considerable similarities between multiple object tracking (MOT) and single object tracking (SOT) tasks, modern MOT methods have not benefited from the development of SOT ones to achieve satisfactory performance.

Multiple Object Tracking Object +2

Enabling Fast and Universal Audio Adversarial Attack Using Generative Model

no code implementations26 Apr 2020 Yi Xie, Zhuohang Li, Cong Shi, Jian Liu, Yingying Chen, Bo Yuan

These idealized assumptions, however, makes the existing audio adversarial attacks mostly impossible to be launched in a timely fashion in practice (e. g., playing unnoticeable adversarial perturbations along with user's streaming input).

Adversarial Attack

Real-time, Universal, and Robust Adversarial Attacks Against Speaker Recognition Systems

no code implementations4 Mar 2020 Yi Xie, Cong Shi, Zhuohang Li, Jian Liu, Yingying Chen, Bo Yuan

As the popularity of voice user interface (VUI) exploded in recent years, speaker recognition system has emerged as an important medium of identifying a speaker in many security-required applications and services.

Adversarial Attack Room Impulse Response (RIR) +1

Spearphone: A Speech Privacy Exploit via Accelerometer-Sensed Reverberations from Smartphone Loudspeakers

1 code implementation12 Jul 2019 S Abhishek Anand, Chen Wang, Jian Liu, Nitesh Saxena, Yingying Chen

In this paper, we build a speech privacy attack that exploits speech reverberations generated from a smartphone's inbuilt loudspeaker captured via a zero-permission motion sensor (accelerometer).

Cryptography and Security

Learning Feature Embeddings for Discriminant Model based Tracking

no code implementations ECCV 2020 Linyu Zheng, Ming Tang, Yingying Chen, Jinqiao Wang, Hanqing Lu

After observing that the features used in most online discriminatively trained trackers are not optimal, in this paper, we propose a novel and effective architecture to learn optimal feature embeddings for online discriminative tracking.

Visual Tracking

BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning

4 code implementations CVPR 2020 Fisher Yu, Haofeng Chen, Xin Wang, Wenqi Xian, Yingying Chen, Fangchen Liu, Vashisht Madhavan, Trevor Darrell

Datasets drive vision progress, yet existing driving datasets are impoverished in terms of visual content and supported tasks to study multitask learning for autonomous driving.

Autonomous Driving Domain Adaptation +8

Fast Deep Matting for Portrait Animation on Mobile Phone

1 code implementation26 Jul 2017 Bingke Zhu, Yingying Chen, Jinqiao Wang, Si Liu, Bo Zhang, Ming Tang

Finally, an automatic portrait animation system based on fast deep matting is built on mobile devices, which does not need any interaction and can realize real-time matting with 15 fps.

Image Matting Video Editing

Joint Background Reconstruction and Foreground Segmentation via A Two-stage Convolutional Neural Network

no code implementations24 Jul 2017 Xu Zhao, Yingying Chen, Ming Tang, Jinqiao Wang

In the first stage, a convolutional encoder-decoder sub-network is employed to reconstruct the background images and encode rich prior knowledge of background scenes.

Decoder Foreground Segmentation +1

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