Search Results for author: Ning Wang

Found 57 papers, 17 papers with code

The Design and Implementation of a Real Time Visual Search System on JD E-commerce Platform

1 code implementation19 Aug 2019 Jie Li, Haifeng Liu, Chuanghua Gui, Jianyu Chen, Zhenyun Ni, Ning Wang

We present the design and implementation of a visual search system for real time image retrieval on JD. com, the world's third largest and China's largest e-commerce site.

Image Retrieval Retrieval

Recurrent Feature Reasoning for Image Inpainting

1 code implementation CVPR 2020 Jingyuan Li, Ning Wang, Lefei Zhang, Bo Du, DaCheng Tao

To capture information from distant places in the feature map for RFR, we further develop KCA and incorporate it in RFR.

Image Inpainting SSIM

Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking

1 code implementation CVPR 2021 Ning Wang, Wengang Zhou, Jie Wang, Houqaing Li

In video object tracking, there exist rich temporal contexts among successive frames, which have been largely overlooked in existing trackers.

Object Video Object Tracking +2

NAS-FCOS: Efficient Search for Object Detection Architectures

1 code implementation24 Oct 2021 Ning Wang, Yang Gao, Hao Chen, Peng Wang, Zhi Tian, Chunhua Shen, Yanning Zhang

Neural Architecture Search (NAS) has shown great potential in effectively reducing manual effort in network design by automatically discovering optimal architectures.

Neural Architecture Search Object +2

SoccerNet 2022 Challenges Results

7 code implementations5 Oct 2022 Silvio Giancola, Anthony Cioppa, Adrien Deliège, Floriane Magera, Vladimir Somers, Le Kang, Xin Zhou, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdulrahman Darwish, Adrien Maglo, Albert Clapés, Andreas Luyts, Andrei Boiarov, Artur Xarles, Astrid Orcesi, Avijit Shah, Baoyu Fan, Bharath Comandur, Chen Chen, Chen Zhang, Chen Zhao, Chengzhi Lin, Cheuk-Yiu Chan, Chun Chuen Hui, Dengjie Li, Fan Yang, Fan Liang, Fang Da, Feng Yan, Fufu Yu, Guanshuo Wang, H. Anthony Chan, He Zhu, Hongwei Kan, Jiaming Chu, Jianming Hu, Jianyang Gu, Jin Chen, João V. B. Soares, Jonas Theiner, Jorge De Corte, José Henrique Brito, Jun Zhang, Junjie Li, Junwei Liang, Leqi Shen, Lin Ma, Lingchi Chen, Miguel Santos Marques, Mike Azatov, Nikita Kasatkin, Ning Wang, Qiong Jia, Quoc Cuong Pham, Ralph Ewerth, Ran Song, RenGang Li, Rikke Gade, Ruben Debien, Runze Zhang, Sangrok Lee, Sergio Escalera, Shan Jiang, Shigeyuki Odashima, Shimin Chen, Shoichi Masui, Shouhong Ding, Sin-wai Chan, Siyu Chen, Tallal El-Shabrawy, Tao He, Thomas B. Moeslund, Wan-Chi Siu, Wei zhang, Wei Li, Xiangwei Wang, Xiao Tan, Xiaochuan Li, Xiaolin Wei, Xiaoqing Ye, Xing Liu, Xinying Wang, Yandong Guo, YaQian Zhao, Yi Yu, YingYing Li, Yue He, Yujie Zhong, Zhenhua Guo, Zhiheng Li

The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team.

Action Spotting Camera Calibration +3

Multi-Cue Correlation Filters for Robust Visual Tracking

1 code implementation CVPR 2018 Ning Wang, Wengang Zhou, Qi Tian, Richang Hong, Meng Wang, Houqiang Li

By combining different types of features, our approach constructs multiple experts through Discriminative Correlation Filter (DCF) and each of them tracks the target independently.

Visual Tracking

Contrastive Transformation for Self-supervised Correspondence Learning

1 code implementation9 Dec 2020 Ning Wang, Wengang Zhou, Houqiang Li

It is worth mentioning that our method also surpasses the fully-supervised affinity representation (e. g., ResNet) and performs competitively against the recent fully-supervised algorithms designed for the specific tasks (e. g., VOT and VOS).

Self-Supervised Learning Semantic Segmentation +3

Joint Inductive and Transductive Learning for Video Object Segmentation

1 code implementation ICCV 2021 Yunyao Mao, Ning Wang, Wengang Zhou, Houqiang Li

In this work, we propose to integrate transductive and inductive learning into a unified framework to exploit the complementarity between them for accurate and robust video object segmentation.

Object Semantic Segmentation +3

A Mountain-Shaped Single-Stage Network for Accurate Image Restoration

1 code implementation9 May 2023 Hu Gao, Jing Yang, Ying Zhang, Ning Wang, Jingfan Yang, Depeng Dang

Image restoration is the task of aiming to obtain a high-quality image from a corrupt input image, such as deblurring and deraining.

Deblurring Image Deblurring +2

SU-Net: Pose estimation network for non-cooperative spacecraft on-orbit

1 code implementation21 Feb 2023 Hu Gao, Zhihui Li, Depeng Dang, Ning Wang, Jingfan Yang

In this way, the feature loss and the complexity of the model is reduced, and the degradation of deep neural network during training is avoided.

Pose Estimation Spacecraft Pose Estimation +1

Real-Time Correlation Tracking via Joint Model Compression and Transfer

1 code implementation23 Jul 2019 Ning Wang, Wengang Zhou, Yibing Song, Chao Ma, Houqiang Li

In the distillation process, we propose a fidelity loss to enable the student network to maintain the representation capability of the teacher network.

Computational Efficiency Image Classification +4

Deep Adaptive Arbitrary Polynomial Chaos Expansion: A Mini-data-driven Semi-supervised Method for Uncertainty Quantification

1 code implementation22 Jul 2021 Wen Yao, Xiaohu Zheng, Jun Zhang, Ning Wang, Guijian Tang

Based on the adaptive aPC, a semi-supervised deep adaptive arbitrary polynomial chaos expansion (Deep aPCE) method is proposed to reduce the training data cost and improve the surrogate model accuracy.

Dimensionality Reduction Uncertainty Quantification

An Online Universal Classifier for Binary, Multi-class and Multi-label Classification

no code implementations3 Sep 2016 Meng Joo Er, Rajasekar Venkatesan, Ning Wang

Several classifiers are developed for binary, multi-class and multi-label classification problems, but there are no classifiers available in the literature capable of performing all three types of classification.

Classification General Classification +1

A High Speed Multi-label Classifier based on Extreme Learning Machines

no code implementations31 Aug 2016 Meng Joo Er, Rajasekar Venkatesan, Ning Wang

In this paper a high speed neural network classifier based on extreme learning machines for multi-label classification problem is proposed and dis-cussed.

Classification General Classification +3

Few-Shot Sequence Labeling with Label Dependency Transfer and Pair-wise Embedding

no code implementations20 Jun 2019 Yutai Hou, Zhihan Zhou, Yijia Liu, Ning Wang, Wanxiang Che, Han Liu, Ting Liu

It calculates emission score with similarity based methods and obtains transition score with a specially designed transfer mechanism.

Few-Shot Learning named-entity-recognition +3

Collecting and Analyzing Multidimensional Data with Local Differential Privacy

no code implementations28 Jun 2019 Ning Wang, Xiaokui Xiao, Yin Yang, Jun Zhao, Siu Cheung Hui, Hyejin Shin, Junbum Shin, Ge Yu

Motivated by this, we first propose novel LDP mechanisms for collecting a numeric attribute, whose accuracy is at least no worse (and usually better) than existing solutions in terms of worst-case noise variance.

Attribute

Local Differential Privacy based Federated Learning for Internet of Things

no code implementations19 Apr 2020 Yang Zhao, Jun Zhao, Mengmeng Yang, Teng Wang, Ning Wang, Lingjuan Lyu, Dusit Niyato, Kwok-Yan Lam

To avoid the privacy threat and reduce the communication cost, in this paper, we propose to integrate federated learning and local differential privacy (LDP) to facilitate the crowdsourcing applications to achieve the machine learning model.

BIG-bench Machine Learning Federated Learning +1

Personalized Early Stage Alzheimer's Disease Detection: A Case Study of President Reagan's Speeches

no code implementations WS 2020 Ning Wang, Fan Luo, Vishal Peddagangireddy, K. P. Subbalakshmi, R. Chandramouli

In this paper, we show that machine learning-based unsupervised clustering of and anomaly detection with linguistic biomarkers are promising approaches for intuitive visualization and personalized early stage detection of Alzheimer`s disease.

Alzheimer's Disease Detection Anomaly Detection +1

Cascaded Regression Tracking: Towards Online Hard Distractor Discrimination

no code implementations18 Jun 2020 Ning Wang, Wengang Zhou, Qi Tian, Houqiang Li

In the second stage, a discrete sampling based ridge regression is designed to double-check the remaining ambiguous hard samples, which serves as an alternative of fully-connected layers and benefits from the closed-form solver for efficient learning.

regression Visual Tracking

Explainable CNN-attention Networks (C-Attention Network) for Automated Detection of Alzheimer's Disease

no code implementations25 Jun 2020 Ning Wang, Mingxuan Chen, K. P. Subbalakshmi

In this work, we propose three explainable deep learning architectures to automatically detect patients with Alzheimer`s disease based on their language abilities.

Explainable Rumor Detection using Inter and Intra-feature Attention Networks

no code implementations21 Jul 2020 Mingxuan Chen, Ning Wang, K. P. Subbalakshmi

With social media becoming ubiquitous, information consumption from this media has also increased.

Benchmarking

Strain engineering of epitaxial oxide heterostructures beyond substrate limitations

no code implementations3 May 2019 Xiong Deng, Chao Chen, Deyang Chen, Xiangbin Cai, Xiaozhe Yin, Chao Xu, Fei Sun, Caiwen Li, Yan Li, Han Xu, Mao Ye, Guo Tian, Zhen Fan, Zhipeng Hou, Minghui Qin, Yu Chen, Zhenlin Luo, Xubing Lu, Guofu Zhou, Lang Chen, Ning Wang, Ye Zhu, Xingsen Gao, Jun-Ming Liu

The limitation of commercially available single-crystal substrates and the lack of continuous strain tunability preclude the ability to take full advantage of strain engineering for further exploring novel properties and exhaustively studying fundamental physics in complex oxides.

Materials Science

Lattice reconstruction induced multiple ultra-flat bands in twisted bilayer WSe2

no code implementations11 Mar 2021 En Li, Jin-Xin Hu, Xuemeng Feng, Zishu Zhou, Liheng An, Kam Tuen Law, Ning Wang, Nian Lin

Moir\'e superlattices in van der Waals heterostructures provide a tunable platform to study emergent properties that are absent in the natural crystal form.

Mesoscale and Nanoscale Physics

CAT: Cross-Attention Transformer for One-Shot Object Detection

no code implementations30 Apr 2021 Weidong Lin, Yuyan Deng, Yang Gao, Ning Wang, Jinghao Zhou, Lingqiao Liu, Lei Zhang, Peng Wang

Given a query patch from a novel class, one-shot object detection aims to detect all instances of that class in a target image through the semantic similarity comparison.

Object object-detection +3

Learning Models for Suicide Prediction from Social Media Posts

no code implementations NAACL (CLPsych) 2021 Ning Wang, Fan Luo, Yuvraj Shivtare, Varsha D. Badal, K. P. Subbalakshmi, R. Chandramouli, Ellen Lee

We propose a deep learning architecture and test three other machine learning models to automatically detect individuals that will attempt suicide within (1) 30 days and (2) six months, using their social media post data provided in the CLPsych 2021 shared task.

BIG-bench Machine Learning

Diff-Net: Image Feature Difference based High-Definition Map Change Detection for Autonomous Driving

no code implementations14 Jul 2021 Lei He, Shengjie Jiang, Xiaoqing Liang, Ning Wang, Shiyu Song

Compared to traditional methods based on object detectors, the essential design in our work is a parallel feature difference calculation structure that infers map changes by comparing features extracted from the camera and rasterized images.

Autonomous Driving Change Detection +3

Spatio-Temporal Interaction Graph Parsing Networks for Human-Object Interaction Recognition

no code implementations19 Aug 2021 Ning Wang, Guangming Zhu, Liang Zhang, Peiyi Shen, Hongsheng Li, Cong Hua

With the effective spatio-temporal relationship modeling, it is possible not only to uncover contextual information in each frame but also to directly capture inter-time dependencies.

Human-Object Interaction Detection Object

M2R2: Missing-Modality Robust emotion Recognition framework with iterative data augmentation

no code implementations5 May 2022 Ning Wang

This paper deals with the utterance-level modalities missing problem with uncertain patterns on emotion recognition in conversation (ERC) task.

Data Augmentation Emotion Recognition in Conversation +2

Adaptive Graph Convolutional Network Framework for Multidimensional Time Series Prediction

no code implementations8 May 2022 Ning Wang

In the real world, long sequence time-series forecasting (LSTF) is needed in many cases, such as power consumption prediction and air quality prediction. Multi-dimensional long time series model has more strict requirements on the model, which not only needs to effectively capture the accurate long-term dependence between input and output, but also needs to capture the relationship between data of different dimensions. Recent research shows that the Informer model based on Transformer has achieved excellent performance in long time series prediction. However, this model still has some deficiencies in multidimensional prediction, it cannot capture the relationship between different dimensions well.

Time Series Time Series Forecasting +1

Intelligent MIMO Detection Using Meta Learning

no code implementations8 Aug 2022 Haomiao Huo, Jindan Xu, Gege Su, Wei Xu, Ning Wang

By treating K as a variable that can be adjusted according to a fitting function of some learnable coefficients, an intelligent MIMO detection network based on deep neural networks (DNN) is proposed to reduce complexity of the detection algorithm with little performance degradation.

Meta-Learning

Controllable Image Captioning via Prompting

no code implementations4 Dec 2022 Ning Wang, Jiahao Xie, Jihao Wu, Mingbo Jia, Linlin Li

Despite the remarkable progress of image captioning, existing captioners typically lack the controllable capability to generate desired image captions, e. g., describing the image in a rough or detailed manner, in a factual or emotional view, etc.

controllable image captioning Prompt Engineering

Efficient Image Captioning for Edge Devices

no code implementations18 Dec 2022 Ning Wang, Jiangrong Xie, Hang Luo, Qinglin Cheng, Jihao Wu, Mingbo Jia, Linlin Li

On the other hand, we transfer the image-text retrieval design of CLIP to image captioning scenarios by devising a novel visual concept extractor and a cross-modal modulator.

Image Captioning Retrieval +1

My Actions Speak Louder Than Your Words: When User Behavior Predicts Their Beliefs about Agents' Attributes

no code implementations21 Jan 2023 Nikolos Gurney, David Pynadath, Ning Wang

An implicit expectation of asking users to rate agents, such as an AI decision-aid, is that they will use only relevant information -- ask them about an agent's benevolence, and they should consider whether or not it was kind.

Comparing Psychometric and Behavioral Predictors of Compliance During Human-AI Interactions

no code implementations3 Feb 2023 Nikolos Gurney, David V. Pynadath, Ning Wang

A common hypothesis in adaptive AI research is that minor differences in people's predisposition to trust can significantly impact their likelihood of complying with recommendations from the AI.

Generative Adversarial Network for Personalized Art Therapy in Melanoma Disease Management

no code implementations16 Mar 2023 Lennart Jütte, Ning Wang, Bernhard Roth

We aim to provide a well-trained image style transfer model that can quickly generate unique art from personal dermoscopic melanoma images as an additional tool for art therapy in disease management of melanoma.

Generative Adversarial Network Management +1

A optimization framework for herbal prescription planning based on deep reinforcement learning

no code implementations25 Apr 2023 Kuo Yang, Zecong Yu, Xin Su, Xiong He, Ning Wang, Qiguang Zheng, Feidie Yu, Zhuang Liu, Tiancai Wen, Xuezhong Zhou

We constructed a high-quality benchmark dataset for sequential diagnosis and treatment of diabetes and evaluated PrescDRL against this benchmark.

reinforcement-learning Sequential Diagnosis

Recyclable Semi-supervised Method Based on Multi-model Ensemble for Video Scene Parsing

no code implementations5 Jun 2023 Biao Wu, Shaoli Liu, Diankai Zhang, Chengjian Zheng, Si Gao, Xiaofeng Zhang, Ning Wang

Pixel-level Scene Understanding is one of the fundamental problems in computer vision, which aims at recognizing object classes, masks and semantics of each pixel in the given image.

Scene Understanding Semantic Segmentation +1

UTILIZING FEDERATED LEARNING AND META LEARNING FOR FEW-SHOT LEARNING ON EDGE DEVICES

no code implementations Rowan University 2022 Anthony Breitzman, Nancy Tinkham, Ning Wang

The efficient and effective handling of few-shot learning tasks on mobile devices is challenging due to the small training set issue and the physical limitations in power and computational resources on these devices.

Federated Learning Few-Shot Learning

RIS-assisted High-Speed Railway Integrated Sensing and Communication System

no code implementations19 Aug 2023 Panpan Li, Yong Niu, Hao Wu, Zhu Han, Guiqi Sun, Ning Wang, Zhangdui Zhong, Bo Ai

One technology that has the potential to improve wireless communications in years to come is integrated sensing and communication (ISAC).

Exploring the relationship between response time sequence in scale answering process and severity of insomnia: a machine learning approach

no code implementations13 Oct 2023 Zhao Su, Rongxun Liu, Keyin Zhou, Xinru Wei, Ning Wang, Zexin Lin, Yuanchen Xie, Jie Wang, Fei Wang, Shenzhong Zhang, Xizhe Zhang

The relationship between symptom severity and response time was explored, and a machine learning model was developed to predict the presence of insomnia.

Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction

no code implementations10 Nov 2023 Shanghao Shi, Ning Wang, Yang Xiao, Chaoyu Zhang, Yi Shi, Y. Thomas Hou, Wenjing Lou

Unlike existing approaches treating models as black boxes, Scale-MIA recognizes the importance of the intricate architecture and inner workings of machine learning models.

Federated Learning

DocBinFormer: A Two-Level Transformer Network for Effective Document Image Binarization

no code implementations6 Dec 2023 Risab Biswas, Swalpa Kumar Roy, Ning Wang, Umapada Pal, Guang-Bin Huang

Instead of using a simple vision transformer block to extract information from the image patches, the proposed architecture uses two transformer blocks for greater coverage of the extracted feature space on a global and local scale.

Binarization

Cycle-Consistency Learning for Captioning and Grounding

no code implementations23 Dec 2023 Ning Wang, Jiajun Deng, Mingbo Jia

The proposed framework (1) allows the semi-weakly supervised training of visual grounding; (2) improves the performance of fully supervised visual grounding; (3) yields a general captioning model that can describe arbitrary image regions.

Image Captioning Visual Grounding

A Video Coding Method Based on Neural Network for CLIC2024

no code implementations8 Jan 2024 Zhengang Li, Jingchi Zhang, Yonghua Wang, Xing Zeng, Zhen Zhang, Yunlin Long, Menghu Jia, Ning Wang

Meanwhile, the deep learning methods propose a convolutional neural network-based loop filter (CNNLF), which is turned on/off based on the rate-distortion optimization at the CTU and frame level.

Quantization

Image classification network enhancement methods based on knowledge injection

no code implementations9 Jan 2024 Yishuang Tian, Ning Wang, Liang Zhang

The current deep neural network algorithm still stays in the end-to-end training supervision method like Image-Label pairs, which makes traditional algorithm is difficult to explain the reason for the results, and the prediction logic is difficult to understand and analyze.

Classification Image Classification

LR-CNN: Lightweight Row-centric Convolutional Neural Network Training for Memory Reduction

no code implementations21 Jan 2024 Zhigang Wang, Hangyu Yang, Ning Wang, Chuanfei Xu, Jie Nie, Zhiqiang Wei, Yu Gu, Ge Yu

However, training its complex network is very space-consuming, since a lot of intermediate data are preserved across layers, especially when processing high-dimension inputs with a big batch size.

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