Search Results for author: Jun Xu

Found 92 papers, 36 papers with code

Dynamic Message Propagation Network for RGB-D Salient Object Detection

no code implementations20 Jun 2022 Baian Chen, Zhilei Chen, Xiaowei Hu, Jun Xu, Haoran Xie, Mingqiang Wei, Jing Qin

This paper presents a novel deep neural network framework for RGB-D salient object detection by controlling the message passing between the RGB images and depth maps on the feature level and exploring the long-range semantic contexts and geometric information on both RGB and depth features to infer salient objects.

object-detection RGB-D Salient Object Detection +1

Person-job fit estimation from candidate profile and related recruitment history with co-attention neural networks

1 code implementation18 Jun 2022 Ziyang Wang, Wei Wei, Chenwei Xu, Jun Xu, Xian-Ling Mao

Existing studies on person-job fit, however, mainly focus on calculating the similarity between the candidate resumes and the job postings on the basis of their contents, without taking the recruiters' experience (i. e., historical successful recruitment records) into consideration.

Semi-Cycled Generative Adversarial Networks for Real-World Face Super-Resolution

1 code implementation8 May 2022 Hao Hou, Xiaotao Hu, Jun Xu, Yingkun Hou, Benzheng Wei, Dinggang Shen

To better exploit the powerful generative capability of GAN for real-world face SR, in this paper, we establish two independent degradation branches in the forward and backward cycle-consistent reconstruction processes, respectively, while the two processes share the same restoration branch.

Image Restoration Super-Resolution

Reinforcement Re-ranking with 2D Grid-based Recommendation Panels

no code implementations11 Apr 2022 Sirui Chen, Xiao Zhang, Xu Chen, Zhiyu Li, YuAn Wang, Quan Lin, Jun Xu

Presenting items in grid-based result panels poses new challenges to recommender systems because existing models are all designed to output sequential lists while the slots in a grid-based panel have no explicit order.

Recommendation Systems Re-Ranking

Fusion-Correction Network for Single-Exposure Correction and Multi-Exposure Fusion

no code implementations5 Mar 2022 Jin Liang, Anran Zhang, Jun Xu, Hui Li, XianTong Zhen

The Single-Exposure Correction (SEC) and Multi-Exposure Fusion (MEF) are two widely studied image processing tasks for image exposure enhancement.

A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems

1 code implementation23 Feb 2022 Yan Lyu, Sunhao Dai, Peng Wu, Quanyu Dai, yuhao deng, Wenjie Hu, Zhenhua Dong, Jun Xu, Shengyu Zhu, Xiao-Hua Zhou

To better support the studies of causal inference and further explanations in recommender systems, we propose a novel semi-synthetic data generation framework for recommender systems where causal graphical models with missingness are employed to describe the causal mechanism of practical recommendation scenarios.

Causal Inference Recommendation Systems +1

A Model-Agnostic Causal Learning Framework for Recommendation using Search Data

1 code implementation9 Feb 2022 Zihua Si, Xueran Han, Xiao Zhang, Jun Xu, Yue Yin, Yang song, Ji-Rong Wen

In this paper, we propose a model-agnostic framework named IV4Rec that can effectively decompose the embedding vectors into these two parts, hence enhancing recommendation results.

Recommendation Systems

Complexity-Oriented Per-shot Video Coding Optimization

no code implementations23 Dec 2021 Hongcheng Zhong, Jun Xu, Chen Zhu, Donghui Feng, Li Song

Current per-shot encoding schemes aim to improve the compression efficiency by shot-level optimization.

A Multi-user Oriented Live Free-viewpoint Video Streaming System Based On View Interpolation

no code implementations20 Dec 2021 Jingchuan Hu, Shuai Guo, Kai Zhou, Yu Dong, Jun Xu, Li Song

As an important application form of immersive multimedia services, free-viewpoint video(FVV) enables users with great immersive experience by strong interaction.

Incremental Cross-view Mutual Distillation for Self-supervised Medical CT Synthesis

no code implementations CVPR 2022 Chaowei Fang, Liang Wang, Dingwen Zhang, Jun Xu, Yixuan Yuan, Junwei Han

Under this circumstance, the models learned from different views can distill valuable knowledge to guide the learning processes of each other.

Self-Supervised Learning

Error-free approximation of explicit linear MPC through lattice piecewise affine expression

no code implementations1 Oct 2021 Jun Xu, Yunjiang Lou

The performance of the proposed approximation strategy is tested through two simulation examples, and the result shows that with a moderate number of sample points, we can construct lattice PWA approximations that are equivalent to optimal control law of the explicit linear MPC.

Partial Information as Full: Reward Imputation with Sketching in Bandits

no code implementations29 Sep 2021 Xiao Zhang, Ninglu Shao, Zihua Si, Jun Xu, Wenhan Wang, Hanjing Su, Ji-Rong Wen

In this paper, we propose an efficient reward imputation approach using sketching in CBB, which completes the unobserved rewards with the imputed rewards approximating the full-information feedbacks.

Imputation

Modeling Relevance Ranking under the Pre-training and Fine-tuning Paradigm

no code implementations12 Aug 2021 Lin Bo, Liang Pang, Gang Wang, Jun Xu, Xiuqiang He, Ji-Rong Wen

Experimental results base on three publicly available benchmarks showed that in both of the implementations, Pre-Rank can respectively outperform the underlying ranking models and achieved state-of-the-art performances.

Document Ranking Information Retrieval +2

Discovering Dialog Structure Graph for Coherent Dialog Generation

no code implementations ACL 2021 Jun Xu, Zeyang Lei, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che

Learning discrete dialog structure graph from human-human dialogs yields basic insights into the structure of conversation, and also provides background knowledge to facilitate dialog generation.

NLHD: A Pixel-Level Non-Local Retinex Model for Low-Light Image Enhancement

no code implementations13 Jun 2021 Hao Hou, Yingkun Hou, Yuxuan Shi, Benzheng Wei, Jun Xu

Then a minimum fusion strategy on the results of these two transforms is utilized to achieve more natural illumination component enhancement.

Low-Light Image Enhancement

A Joint Model for Dropped Pronoun Recovery and Conversational Discourse Parsing in Chinese Conversational Speech

1 code implementation ACL 2021 Jingxuan Yang, Kerui Xu, Jun Xu, Si Li, Sheng Gao, Jun Guo, Nianwen Xue, Ji-Rong Wen

A second (multi-relational) GCN is then applied to the utterance states to produce a discourse relation-augmented representation for the utterances, which are then fused together with token states in each utterance as input to a dropped pronoun recovery layer.

Discourse Parsing

MetaKernel: Learning Variational Random Features with Limited Labels

no code implementations8 May 2021 Yingjun Du, Haoliang Sun, XianTong Zhen, Jun Xu, Yilong Yin, Ling Shao, Cees G. M. Snoek

Specifically, we propose learning variational random features in a data-driven manner to obtain task-specific kernels by leveraging the shared knowledge provided by related tasks in a meta-learning setting.

Few-Shot Image Classification Variational Inference

Temporal Modulation Network for Controllable Space-Time Video Super-Resolution

1 code implementation CVPR 2021 Gang Xu, Jun Xu, Zhen Li, Liang Wang, Xing Sun, Ming-Ming Cheng

To well exploit the temporal information, we propose a Locally-temporal Feature Comparison (LFC) module, along with the Bi-directional Deformable ConvLSTM, to extract short-term and long-term motion cues in videos.

Space-time Video Super-resolution Video Super-Resolution

Privacy-preserving Channel Estimation in Cell-free Hybrid Massive MIMO Systems

no code implementations26 Jan 2021 Jun Xu, Xiaodong Wang, Pengcheng Zhu, Xiaohu You

We consider a cell-free hybrid massive multiple-input multiple-output (MIMO) system with $K$ users and $M$ access points (APs), each with $N_a$ antennas and $N_r< N_a$ radio frequency (RF) chains.

Low-Rank Matrix Completion Information Theory Signal Processing Information Theory

Discovering Dialog Structure Graph for Open-Domain Dialog Generation

no code implementations31 Dec 2020 Jun Xu, Zeyang Lei, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che, Ting Liu

Learning interpretable dialog structure from human-human dialogs yields basic insights into the structure of conversation, and also provides background knowledge to facilitate dialog generation.

Open-Domain Dialog

MobileSal: Extremely Efficient RGB-D Salient Object Detection

1 code implementation24 Dec 2020 Yu-Huan Wu, Yun Liu, Jun Xu, Jia-Wang Bian, Yu-Chao Gu, Ming-Ming Cheng

Therefore, we propose an implicit depth restoration (IDR) technique to strengthen the mobile networks' feature representation capability for RGB-D SOD.

object-detection RGB-D Salient Object Detection +1

ICNet: Intra-saliency Correlation Network for Co-Saliency Detection

1 code implementation NeurIPS 2020 Wen-Da Jin, Jun Xu, Ming-Ming Cheng, Yi Zhang, Wei Guo

Intra-saliency and inter-saliency cues have been extensively studied for co-saliency detection (Co-SOD).

Saliency Detection

Transformer-GCRF: Recovering Chinese Dropped Pronouns with General Conditional Random Fields

1 code implementation Findings of the Association for Computational Linguistics 2020 Jingxuan Yang, Kerui Xu, Jun Xu, Si Li, Sheng Gao, Jun Guo, Ji-Rong Wen, Nianwen Xue

Exploratory analysis also demonstrates that the GCRF did help to capture the dependencies between pronouns in neighboring utterances, thus contributes to the performance improvements.

Machine Translation Translation

SparTerm: Learning Term-based Sparse Representation for Fast Text Retrieval

no code implementations2 Oct 2020 Yang Bai, Xiaoguang Li, Gang Wang, Chaoliang Zhang, Lifeng Shang, Jun Xu, Zhaowei Wang, Fangshan Wang, Qun Liu

Term-based sparse representations dominate the first-stage text retrieval in industrial applications, due to its advantage in efficiency, interpretability, and exact term matching.

Language Modelling

Pre-training for Video Captioning Challenge 2020 Summary

no code implementations27 Jul 2020 Yingwei Pan, Jun Xu, Yehao Li, Ting Yao, Tao Mei

The Pre-training for Video Captioning Challenge 2020 Summary: results and challenge participants' technical reports.

Video Captioning

Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient

no code implementations25 Jul 2020 Haonan Jia, Xiao Zhang, Jun Xu, Wei Zeng, Hao Jiang, Xiaohui Yan, Ji-Rong Wen

Deep Q-learning algorithms often suffer from poor gradient estimations with an excessive variance, resulting in unstable training and poor sampling efficiency.

Q-Learning reinforcement-learning

Auto-captions on GIF: A Large-scale Video-sentence Dataset for Vision-language Pre-training

no code implementations5 Jul 2020 Yingwei Pan, Yehao Li, Jianjie Luo, Jun Xu, Ting Yao, Tao Mei

In this work, we present Auto-captions on GIF, which is a new large-scale pre-training dataset for generic video understanding.

Question Answering Video Captioning +2

Interactive Knowledge Distillation

no code implementations3 Jul 2020 Shipeng Fu, Zhen Li, Jun Xu, Ming-Ming Cheng, Zitao Liu, Xiaomin Yang

Knowledge distillation is a standard teacher-student learning framework to train a light-weight student network under the guidance of a well-trained large teacher network.

Knowledge Distillation

Conversational Graph Grounded Policy Learning for Open-Domain Conversation Generation

no code implementations ACL 2020 Jun Xu, Haifeng Wang, Zheng-Yu Niu, Hua Wu, Wanxiang Che, Ting Liu

To address the challenge of policy learning in open-domain multi-turn conversation, we propose to represent prior information about dialog transitions as a graph and learn a graph grounded dialog policy, aimed at fostering a more coherent and controllable dialog.

Response Generation

Learning to Learn Kernels with Variational Random Features

1 code implementation ICML 2020 Xiantong Zhen, Haoliang Sun, Ying-Jun Du, Jun Xu, Yilong Yin, Ling Shao, Cees Snoek

We propose meta variational random features (MetaVRF) to learn adaptive kernels for the base-learner, which is developed in a latent variable model by treating the random feature basis as the latent variable.

Few-Shot Learning Variational Inference

Bilateral Attention Network for RGB-D Salient Object Detection

1 code implementation30 Apr 2020 Zhao Zhang, Zheng Lin, Jun Xu, Wenda Jin, Shao-Ping Lu, Deng-Ping Fan

To better explore salient information in both foreground and background regions, this paper proposes a Bilateral Attention Network (BiANet) for the RGB-D SOD task.

object-detection RGB-D Salient Object Detection +2

Gradient-Induced Co-Saliency Detection

1 code implementation ECCV 2020 Zhao Zhang, Wenda Jin, Jun Xu, Ming-Ming Cheng

Co-saliency detection (Co-SOD) aims to segment the common salient foreground in a group of relevant images.

Co-Salient Object Detection

Conditional Variational Image Deraining

1 code implementation23 Apr 2020 Ying-Jun Du, Jun Xu, Xian-Tong Zhen, Ming-Ming Cheng, Ling Shao

In this paper, we propose a Conditional Variational Image Deraining (CVID) network for better deraining performance, leveraging the exclusive generative ability of Conditional Variational Auto-Encoder (CVAE) on providing diverse predictions for the rainy image.

Density Estimation Rain Removal

JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation

1 code implementation15 Apr 2020 Yu-Huan Wu, Shang-Hua Gao, Jie Mei, Jun Xu, Deng-Ping Fan, Rong-Guo Zhang, Ming-Ming Cheng

The chest CT scan test provides a valuable complementary tool to the RT-PCR test, and it can identify the patients in the early-stage with high sensitivity.

COVID-19 Diagnosis General Classification

Deep Hough Transform for Semantic Line Detection

1 code implementation ECCV 2020 Kai Zhao, Qi Han, Chang-Bin Zhang, Jun Xu, Ming-Ming Cheng

In addition to the proposed method, we design an evaluation metric to assess the quality of line detection and construct a large scale dataset for the line detection task.

Line Detection object-detection

SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval

2 code implementations12 Dec 2019 Liang Pang, Jun Xu, Qingyao Ai, Yanyan Lan, Xue-Qi Cheng, Ji-Rong Wen

In learning-to-rank for information retrieval, a ranking model is automatically learned from the data and then utilized to rank the sets of retrieved documents.

Information Retrieval Learning-To-Rank

Non-negative Sparse and Collaborative Representation for Pattern Classification

no code implementations20 Aug 2019 Jun Xu, Zhou Xu, Wangpeng An, Haoqian Wang, David Zhang

In this paper, we propose a novel Non-negative Sparse and Collaborative Representation (NSCR) for pattern classification.

Classification Face Recognition +1

RANet: Ranking Attention Network for Fast Video Object Segmentation

2 code implementations ICCV 2019 Ziqin Wang, Jun Xu, Li Liu, Fan Zhu, Ling Shao

Specifically, to integrate the insights of matching based and propagation based methods, we employ an encoder-decoder framework to learn pixel-level similarity and segmentation in an end-to-end manner.

online learning Semantic Segmentation +2

HorNet: A Hierarchical Offshoot Recurrent Network for Improving Person Re-ID via Image Captioning

no code implementations14 Aug 2019 Shi-Yang Yan, Jun Xu, Yuai Liu, Lin Xu

Then the proposed HorNet can learn the visual and language representation from both the images and captions jointly, and thus enhance the performance of person re-ID.

Image Captioning Person Re-Identification

Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition

no code implementations11 Aug 2019 Haoqian Wang, Zhiwei Xu, Jun Xu, Wangpeng An, Lei Zhang, Qionghai Dai

There are two main problems in label inference: how to measure the confidence of the unlabeled data and how to generalize the classifier.

Neural or Statistical: An Empirical Study on Language Models for Chinese Input Recommendation on Mobile

no code implementations9 Jul 2019 Hainan Zhang, Yanyan Lan, Jiafeng Guo, Jun Xu, Xue-Qi Cheng

Chinese input recommendation plays an important role in alleviating human cost in typing Chinese words, especially in the scenario of mobile applications.

Language Modelling

SAVIOR: Towards Bug-Driven Hybrid Testing

no code implementations18 Jun 2019 Yao-Hui Chen, Peng Li, Jun Xu, Shengjian Guo, Rundong Zhou, Yulong Zhang, Taowei, Long Lu

Unlike the existing hybrid testing tools, SAVIOR prioritizes the concolic execution of the seeds that are likely to uncover more vulnerabilities.

Software Engineering

NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising

1 code implementation17 Jun 2019 Yingkun Hou, Jun Xu, Mingxia Liu, Guanghai Liu, Li Liu, Fan Zhu, Ling Shao

This is motivated by the fact that finding closely similar pixels is more feasible than similar patches in natural images, which can be used to enhance image denoising performance.

Image Denoising

Noisy-As-Clean: Learning Self-supervised Denoising from the Corrupted Image

1 code implementation17 Jun 2019 Jun Xu, Yuan Huang, Ming-Ming Cheng, Li Liu, Fan Zhu, Zhou Xu, Ling Shao

A simple but useful observation on our NAC is: as long as the noise is weak, it is feasible to learn a self-supervised network only with the corrupted image, approximating the optimal parameters of a supervised network learned with pairs of noisy and clean images.

Image Denoising

STAR: A Structure and Texture Aware Retinex Model

1 code implementation16 Jun 2019 Jun Xu, Yingkun Hou, Dongwei Ren, Li Liu, Fan Zhu, Mengyang Yu, Haoqian Wang, Ling Shao

A novel Structure and Texture Aware Retinex (STAR) model is further proposed for illumination and reflectance decomposition of a single image.

Low-Light Image Enhancement

Generating Multiple Diverse Responses with Multi-Mapping and Posterior Mapping Selection

1 code implementation5 Jun 2019 Chaotao Chen, Jinhua Peng, Fan Wang, Jun Xu, Hua Wu

In this paper, we propose a multi-mapping mechanism to better capture the one-to-many relationship, where multiple mapping modules are employed as latent mechanisms to model the semantic mappings from an input post to its diverse responses.

PTrix: Efficient Hardware-Assisted Fuzzing for COTS Binary

1 code implementation25 May 2019 Yao-Hui Chen, Dongliang Mu, Jun Xu, Zhichuang Sun, Wenbo Shen, Xinyu Xing, Long Lu, Bing Mao

This poor performance is caused by the slow extraction of code coverage information from highly compressed PT traces.

Software Engineering Cryptography and Security

Efficient hinging hyperplanes neural network and its application in nonlinear system identification

no code implementations15 May 2019 Jun Xu, Qinghua Tao, Zhen Li, Xiangming Xi, Johan A. K. Suykens, Shuning Wang

It is proved that for every EHH neural network, there is an equivalent adaptive hinging hyperplanes (AHH) tree, which was also proposed based on the model of HH and find good applications in system identification.

Variable Selection

SeriesNet:A Generative Time Series Forecasting Model

no code implementations 2018 International Joint Conference on Neural Networks (IJCNN) 2018 Zhipeng Shen, Yuanming Zhang ∗, Jiawei Lu, Jun Xu, Gang Xiao

This model can learn multi-range and multi-level features from time series data, and has higher predictive accuracy compared those models using fixed time intervals.

Time Series Time Series Forecasting

Scaled Simplex Representation for Subspace Clustering

3 code implementations26 Jul 2018 Jun Xu, Mengyang Yu, Ling Shao, WangMeng Zuo, Deyu Meng, Lei Zhang, David Zhang

However, the negative entries in the coefficient matrix are forced to be positive when constructing the affinity matrix via exponentiation, absolute symmetrization, or squaring operations.

Tailored Sequence to Sequence Models to Different Conversation Scenarios

no code implementations ACL 2018 Hainan Zhang, Yanyan Lan, Jiafeng Guo, Jun Xu, Xue-Qi Cheng

In this paper, we propose two tailored optimization criteria for Seq2Seq to different conversation scenarios, i. e., the maximum generated likelihood for specific-requirement scenario, and the conditional value-at-risk for diverse-requirement scenario.

Dialogue Generation Response Generation

Sparse, Collaborative, or Nonnegative Representation: Which Helps Pattern Classification?

1 code implementation12 Jun 2018 Jun Xu, Wangpeng An, Lei Zhang, David Zhang

The use of sparse representation (SR) and collaborative representation (CR) for pattern classification has been widely studied in tasks such as face recognition and object categorization.

Classification Face Recognition +2

A PID Controller Approach for Stochastic Optimization of Deep Networks

3 code implementations CVPR 2018 Wangpeng An, Haoqian Wang, Qingyun Sun, Jun Xu, Qionghai Dai, Lei Zhang

We first reveal the intrinsic connections between SGD-Momentum and PID based controller, then present the optimization algorithm which exploits the past, current, and change of gradients to update the network parameters.

Stochastic Optimization

A Hybrid l1-l0 Layer Decomposition Model for Tone Mapping

no code implementations CVPR 2018 Zhetong Liang, Jun Xu, David Zhang, Zisheng Cao, Lei Zhang

State-of-the-art tone mapping algorithms mostly decompose an image into a base layer and a detail layer, and process them accordingly.

Tone Mapping

Modeling Diverse Relevance Patterns in Ad-hoc Retrieval

2 code implementations SIGIR '18 2018 Yixing Fan, Jiafeng Guo, Yanyan Lan, Jun Xu, ChengXiang Zhai, Xue-Qi Cheng

The local matching layer focuses on producing a set of local relevance signals by modeling the semantic matching between a query and each passage of a document.

A Tree Search Algorithm for Sequence Labeling

1 code implementation29 Apr 2018 Yadi Lao, Jun Xu, Yanyan Lan, Jiafeng Guo, Sheng Gao, Xue-Qi Cheng

Inspired by the success and methodology of the AlphaGo Zero, MM-Tag formalizes the problem of sequence tagging with a Monte Carlo tree search (MCTS) enhanced Markov decision process (MDP) model, in which the time steps correspond to the positions of words in a sentence from left to right, and each action corresponds to assign a tag to a word.

Chunking Decision Making +2

MQGrad: Reinforcement Learning of Gradient Quantization in Parameter Server

no code implementations22 Apr 2018 Guoxin Cui, Jun Xu, Wei Zeng, Yanyan Lan, Jiafeng Guo, Xue-Qi Cheng

One of the most significant bottleneck in training large scale machine learning models on parameter server (PS) is the communication overhead, because it needs to frequently exchange the model gradients between the workers and servers during the training iterations.

Quantization reinforcement-learning

Real-world Noisy Image Denoising: A New Benchmark

2 code implementations7 Apr 2018 Jun Xu, Hui Li, Zhetong Liang, David Zhang, Lei Zhang

In order to promote the study on this problem while implementing the concurrent real-world image denoising datasets, we construct a new benchmark dataset which contains comprehensive real-world noisy images of different natural scenes.

Image Denoising

Optimize transfer learning for lung diseases in bronchoscopy using a new concept: sequential fine-tuning

no code implementations10 Feb 2018 Tao Tan, Zhang Li, Haixia Liu, Ping Liu, Wenfang Tang, Hui Li, Yue Sun, Yusheng Yan, Keyu Li, Tao Xu, Shanshan Wan, Ke Lou, Jun Xu, Huiming Ying, Quchang Ouyang, Yuling Tang, Zheyu Hu, Qiang Li

To help doctors to be more selective on biopsies and provide a second opinion on diagnosis, in this work, we propose a computer-aided diagnosis (CAD) system for lung diseases including cancers and tuberculosis (TB).

Transfer Learning

Locally Smoothed Neural Networks

1 code implementation22 Nov 2017 Liang Pang, Yanyan Lan, Jun Xu, Jiafeng Guo, Xue-Qi Cheng

The main idea is to represent the weight matrix of the locally connected layer as the product of the kernel and the smoother, where the kernel is shared over different local receptive fields, and the smoother is for determining the importance and relations of different local receptive fields.

Face Verification Question Answering +1

A Deep Investigation of Deep IR Models

no code implementations24 Jul 2017 Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, Xue-Qi Cheng

Therefore, it is necessary to identify the difference between automatically learned features by deep IR models and hand-crafted features used in traditional learning to rank approaches.

Information Retrieval Learning-To-Rank

Spherical Paragraph Model

no code implementations18 Jul 2017 Ruqing Zhang, Jiafeng Guo, Yanyan Lan, Jun Xu, Xue-Qi Cheng

Representing texts as fixed-length vectors is central to many language processing tasks.

Natural Language Processing Representation Learning +1

Multi-channel Weighted Nuclear Norm Minimization for Real Color Image Denoising

no code implementations ICCV 2017 Jun Xu, Lei Zhang, David Zhang, Xiangchu Feng

Most of the existing denoising algorithms are developed for grayscale images, while it is not a trivial work to extend them for color image denoising because the noise statistics in R, G, B channels can be very different for real noisy images.

Color Image Denoising Image Denoising

External Prior Guided Internal Prior Learning for Real-World Noisy Image Denoising

no code implementations12 May 2017 Jun Xu, Lei Zhang, David Zhang

We propose to exploit the information in both external data and the given noisy image, and develop an external prior guided internal prior learning method for real-world noisy image denoising.

Image Denoising

A Unified Architecture for Semantic Role Labeling and Relation Classification

no code implementations COLING 2016 Jiang Guo, Wanxiang Che, Haifeng Wang, Ting Liu, Jun Xu

This paper describes a unified neural architecture for identifying and classifying multi-typed semantic relations between words in a sentence.

Classification Feature Engineering +7

Internet of Things Applications: Animal Monitoring with Unmanned Aerial Vehicle

no code implementations17 Oct 2016 Jun Xu, Gurkan Solmaz, Rouhollah Rahmatizadeh, Damla Turgut, Ladislau Boloni

To achieve the information efficiently, we propose a path planning approach for the UAV based on a Markov decision process (MDP) model.

Q-Learning Traveling Salesman Problem

A Study of MatchPyramid Models on Ad-hoc Retrieval

1 code implementation15 Jun 2016 Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, Xue-Qi Cheng

Although ad-hoc retrieval can also be formalized as a text matching task, few deep models have been tested on it.

Machine Translation Paraphrase Identification +3

MSR-VTT: A Large Video Description Dataset for Bridging Video and Language

no code implementations CVPR 2016 Jun Xu, Tao Mei, Ting Yao, Yong Rui

In this paper we present MSR-VTT (standing for "ABC-Video to Text") which is a new large-scale video benchmark for video understanding, especially the emerging task of translating video to text.

Image Captioning Video Description +1

Match-SRNN: Modeling the Recursive Matching Structure with Spatial RNN

1 code implementation15 Apr 2016 Shengxian Wan, Yanyan Lan, Jun Xu, Jiafeng Guo, Liang Pang, Xue-Qi Cheng

In this paper, we propose to view the generation of the global interaction between two texts as a recursive process: i. e. the interaction of two texts at each position is a composition of the interactions between their prefixes as well as the word level interaction at the current position.

Semantic Regularities in Document Representations

no code implementations24 Mar 2016 Fei Sun, Jiafeng Guo, Yanyan Lan, Jun Xu, Xue-Qi Cheng

Recent work exhibited that distributed word representations are good at capturing linguistic regularities in language.

Text Matching as Image Recognition

7 code implementations20 Feb 2016 Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, Shengxian Wan, Xue-Qi Cheng

An effective way is to extract meaningful matching patterns from words, phrases, and sentences to produce the matching score.

Ad-Hoc Information Retrieval Natural Language Processing +1

Patch Group Based Nonlocal Self-Similarity Prior Learning for Image Denoising

no code implementations ICCV 2015 Jun Xu, Lei Zhang, WangMeng Zuo, David Zhang, Xiangchu Feng

PGs are extracted from training images by putting nonlocal similar patches into groups, and a PG based Gaussian Mixture Model (PG-GMM) learning algorithm is developed to learn the NSS prior.

Image Denoising

A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations

1 code implementation26 Nov 2015 Shengxian Wan, Yanyan Lan, Jiafeng Guo, Jun Xu, Liang Pang, Xue-Qi Cheng

Our model has several advantages: (1) By using Bi-LSTM, rich context of the whole sentence is leveraged to capture the contextualized local information in each positional sentence representation; (2) By matching with multiple positional sentence representations, it is flexible to aggregate different important contextualized local information in a sentence to support the matching; (3) Experiments on different tasks such as question answering and sentence completion demonstrate the superiority of our model.

Information Retrieval Question Answering +1

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