Search Results for author: Jian Zhang

Found 179 papers, 48 papers with code

Ray Priors through Reprojection: Improving Neural Radiance Fields for Novel View Extrapolation

no code implementations12 May 2022 Jian Zhang, Yuanqing Zhang, Huan Fu, Xiaowei Zhou, Bowen Cai, Jinchi Huang, Rongfei Jia, Binqiang Zhao, Xing Tang

Neural Radiance Fields (NeRF) have emerged as a potent paradigm for representing scenes and synthesizing photo-realistic images.

Image Generation

Metric Learning based Interactive Modulation for Real-World Super-Resolution

no code implementations10 May 2022 Chong Mou, Yanze Wu, Xintao Wang, Chao Dong, Jian Zhang, Ying Shan

Instead of using known degradation levels as explicit supervision to the interactive mechanism, we propose a metric learning strategy to map the unquantifiable degradation levels in real-world scenarios to a metric space, which is trained in an unsupervised manner.

Image Restoration Metric Learning +1

Deep Generalized Unfolding Networks for Image Restoration

1 code implementation28 Apr 2022 Chong Mou, Qian Wang, Jian Zhang

Concretely, without loss of interpretability, we integrate a gradient estimation strategy into the gradient descent step of the Proximal Gradient Descent (PGD) algorithm, driving it to deal with complex and real-world image degradation.

Image Restoration

Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering

1 code implementation26 Apr 2022 Minghao Zhao, Le Wu, Yile Liang, Lei Chen, Jian Zhang, Qilin Deng, Kai Wang, Xudong Shen, Tangjie Lv, Runze Wu

While conventional CF models are known for facing the challenges of the popularity bias that favors popular items, one may wonder "Whether the existing graph-based CF models alleviate or exacerbate popularity bias of recommender systems?"

Collaborative Filtering Recommendation Systems

Learning Weighting Map for Bit-Depth Expansion within a Rational Range

1 code implementation26 Apr 2022 Yuqing Liu, Qi Jia, Jian Zhang, Xin Fan, Shanshe Wang, Siwei Ma, Wen Gao

Existing BDE methods have no unified solution for various BDE situations, and directly learn a mapping for each pixel from LBD image to the desired value in HBD image, which may change the given high-order bits and lead to a huge deviation from the ground truth.


PUERT: Probabilistic Under-sampling and Explicable Reconstruction Network for CS-MRI

1 code implementation24 Apr 2022 Jingfen Xie, Jian Zhang, Yongbing Zhang, Xiangyang Ji

Compressed Sensing MRI (CS-MRI) aims at reconstructing de-aliased images from sub-Nyquist sampling k-space data to accelerate MR Imaging, thus presenting two basic issues, i. e., where to sample and how to reconstruct.


R-DFCIL: Relation-Guided Representation Learning for Data-Free Class Incremental Learning

no code implementations24 Mar 2022 Qiankun Gao, Chen Zhao, Bernard Ghanem, Jian Zhang

After RRL, the classification head is fine-tuned with global class-balanced classification loss to address the data imbalance issue as well as learn the decision boundary between new and previous classes.

class-incremental learning Incremental Learning +2

A Prompting-based Approach for Adversarial Example Generation and Robustness Enhancement

no code implementations21 Mar 2022 Yuting Yang, Pei Huang, Juan Cao, Jintao Li, Yun Lin, Jin Song Dong, Feifei Ma, Jian Zhang

Our attack technique targets the inherent vulnerabilities of NLP models, allowing us to generate samples even without interacting with the victim NLP model, as long as it is based on pre-trained language models (PLMs).

Adversarial Attack

Series Photo Selection via Multi-view Graph Learning

no code implementations18 Mar 2022 Jin Huang, Lu Zhang, Yongshun Gong, Jian Zhang, Xiushan Nie, Yilong Yin

Series photo selection (SPS) is an important branch of the image aesthetics quality assessment, which focuses on finding the best one from a series of nearly identical photos.

Aesthetics Quality Assessment Graph Learning

Panini-Net: GAN Prior Based Degradation-Aware Feature Interpolation for Face Restoration

1 code implementation16 Mar 2022 Yinhuai Wang, Yujie Hu, Jian Zhang

Emerging high-quality face restoration (FR) methods often utilize pre-trained GAN models (\textit{i. e.}, StyleGAN2) as GAN Prior.

Representation Learning Super-Resolution

NeRFocus: Neural Radiance Field for 3D Synthetic Defocus

no code implementations10 Mar 2022 Yinhuai Wang, Shuzhou Yang, Yujie Hu, Jian Zhang

Unlike the pinhole, the thin lens refracts rays of a scene point, so its imaging on the sensor plane is scattered as a circle of confusion (CoC).

Unsupervised Learning on 3D Point Clouds by Clustering and Contrasting

no code implementations5 Feb 2022 Guofeng Mei, Litao Yu, Qiang Wu, Jian Zhang, Mohammed Bennamoun

This paper proposes a general unsupervised approach, named \textbf{ConClu}, to perform the learning of point-wise and global features by jointly leveraging point-level clustering and instance-level contrasting.

3D Object Classification Representation Learning +1

Quantifying Robustness to Adversarial Word Substitutions

no code implementations11 Jan 2022 Yuting Yang, Pei Huang, Feifei Ma, Juan Cao, Meishan Zhang, Jian Zhang, Jintao Li

Deep-learning-based NLP models are found to be vulnerable to word substitution perturbations.

CSformer: Bridging Convolution and Transformer for Compressive Sensing

no code implementations31 Dec 2021 Dongjie Ye, Zhangkai Ni, Hanli Wang, Jian Zhang, Shiqi Wang, Sam Kwong

The proposed approach is an end-to-end compressive image sensing method, composed of adaptive sampling and recovery.

Compressive Sensing Representation Learning

COTReg:Coupled Optimal Transport based Point Cloud Registration

no code implementations29 Dec 2021 Guofeng Mei, Xiaoshui Huang, Litao Yu, Jian Zhang, Mohammed Bennamoun

Generating a set of high-quality correspondences or matches is one of the most critical steps in point cloud registration.

Point Cloud Registration

More is Better: A Novel Multi-view Framework for Domain Generalization

no code implementations23 Dec 2021 Jian Zhang, Lei Qi, Yinghuan Shi, Yang Gao

In test stage, to alleviate unstable prediction, we utilize multiple augmented images to yield multi-view prediction, which significantly promotes model reliability via fusing the results of different views of a test image.

Domain Generalization Meta-Learning

HerosNet: Hyperspectral Explicable Reconstruction and Optimal Sampling Deep Network for Snapshot Compressive Imaging

1 code implementation12 Dec 2021 Xuanyu Zhang, Yongbing Zhang, Ruiqin Xiong, Qilin Sun, Jian Zhang

Hyperspectral imaging is an essential imaging modality for a wide range of applications, especially in remote sensing, agriculture, and medicine.

Compressive Sensing

GenReg: Deep Generative Method for Fast Point Cloud Registration

no code implementations23 Nov 2021 Xiaoshui Huang, Zongyi Xu, Guofeng Mei, Sheng Li, Jian Zhang, Yifan Zuo, Yucheng Wang

To solve this challenge, we propose a new data-driven registration algorithm by investigating deep generative neural networks to point cloud registration.

Point Cloud Registration

Can Graph Neural Networks Learn to Solve MaxSAT Problem?

no code implementations15 Nov 2021 Minghao Liu, Fuqi Jia, Pei Huang, Fan Zhang, Yuchen Sun, Shaowei Cai, Feifei Ma, Jian Zhang

With the rapid development of deep learning techniques, various recent work has tried to apply graph neural networks (GNNs) to solve NP-hard problems such as Boolean Satisfiability (SAT), which shows the potential in bridging the gap between machine learning and symbolic reasoning.

ε-weakened Robustness of Deep Neural Networks

no code implementations29 Oct 2021 Pei Huang, Yuting Yang, Minghao Liu, Fuqi Jia, Feifei Ma, Jian Zhang

This paper introduces a notation of $\varepsilon$-weakened robustness for analyzing the reliability and stability of deep neural networks (DNNs).

Research on the inverse kinematics prediction of a soft biomimetic actuator via BP neural network

no code implementations26 Oct 2021 Huichen Ma, Junjie Zhou, Jian Zhang, Lingyu Zhang

On the other hand, the material model is a complicated system with significant nonlinearity, non-stationarity, and uncertainty, making it challenging to develop an appropriate system model.

Motion Planning

Memory-Augmented Deep Unfolding Network for Compressive Sensing

1 code implementation19 Oct 2021 Jiechong Song, Bin Chen, Jian Zhang

By understanding DUNs from the perspective of the human brain's memory processing, we find there exists two issues in existing DUNs.

Compressive Sensing

Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation

1 code implementation17 Oct 2021 Yinghuan Shi, Jian Zhang, Tong Ling, Jiwen Lu, Yefeng Zheng, Qian Yu, Lei Qi, Yang Gao

In semi-supervised medical image segmentation, most previous works draw on the common assumption that higher entropy means higher uncertainty.

Semantic Segmentation Semi-supervised Medical Image Segmentation

Dyn-Backdoor: Backdoor Attack on Dynamic Link Prediction

no code implementations8 Oct 2021 Jinyin Chen, Haiyang Xiong, Haibin Zheng, Jian Zhang, Guodong Jiang, Yi Liu

Backdoor attacks induce the DLP methods to make wrong prediction by the malicious training data, i. e., generating a subgraph sequence as the trigger and embedding it to the training data.

Backdoor Attack Dynamic Link Prediction

Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging

1 code implementation ICCV 2021 Zhuoyuan Wu, Jian Zhang, Chong Mou

To better exploit the spatial-temporal correlation among frames and address the problem of information loss between adjacent phases in existing DUNs, we propose to adopt the 3D-CNN prior in our proximal mapping module and develop a novel dense feature map (DFM) strategy, respectively.

Dynamic Attentive Graph Learning for Image Restoration

1 code implementation ICCV 2021 Chong Mou, Jian Zhang, Zhuoyuan Wu

Specifically, we propose an improved graph model to perform patch-wise graph convolution with a dynamic and adaptive number of neighbors for each node.

Demosaicking Graph Learning +1

Structure Destruction and Content Combination for Face Anti-Spoofing

no code implementations22 Jul 2021 Ke-Yue Zhang, Taiping Yao, Jian Zhang, Shice Liu, Bangjie Yin, Shouhong Ding, Jilin Li

In pursuit of consolidating the face verification systems, prior face anti-spoofing studies excavate the hidden cues in original images to discriminate real persons and diverse attack types with the assistance of auxiliary supervision.

Face Anti-Spoofing Face Verification

Multi-Level Contrastive Learning for Few-Shot Problems

no code implementations15 Jul 2021 Qing Chen, Jian Zhang

Most current applications of contrastive learning benefit only a single representation from the last layer of an encoder. In this paper, we propose a multi-level contrasitive learning approach which applies contrastive losses at different layers of an encoder to learn multiple representations from the encoder.

Contrastive Learning Few-Shot Learning

COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing

1 code implementation15 Jul 2021 Di You, Jian Zhang, Jingfen Xie, Bin Chen, Siwei Ma

In this paper, we propose a novel COntrollable Arbitrary-Sampling neTwork, dubbed COAST, to solve CS problems of arbitrary-sampling matrices (including unseen sampling matrices) with one single model.

Compressive Sensing

Learning Disentangled Representation Implicitly via Transformer for Occluded Person Re-Identification

no code implementations6 Jul 2021 Mengxi Jia, Xinhua Cheng, Shijian Lu, Jian Zhang

To better eliminate interference from occlusions, we design a contrast feature learning technique (CFL) for better separation of occlusion features and discriminative ID features.

Person Re-Identification Representation Learning

Spk2ImgNet: Learning To Reconstruct Dynamic Scene From Continuous Spike Stream

no code implementations CVPR 2021 Jing Zhao, Ruiqin Xiong, Hangfan Liu, Jian Zhang, Tiejun Huang

Different from the conventional digital cameras that compact the photoelectric information within the exposure interval into a single snapshot, the spike camera produces a continuous spike stream to record the dynamic light intensity variation process.

Image Reconstruction

A Multi-Branch Hybrid Transformer Networkfor Corneal Endothelial Cell Segmentation

no code implementations21 May 2021 Yinglin Zhang, Risa Higashita, Huazhu Fu, Yanwu Xu, Yang Zhang, Haofeng Liu, Jian Zhang, Jiang Liu

Corneal endothelial cell segmentation plays a vital role inquantifying clinical indicators such as cell density, coefficient of variation, and hexagonality.

Cell Segmentation

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

2 code implementations17 May 2021 Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh

Offline Reinforcement Learning promises to learn effective policies from previously-collected, static datasets without the need for exploration.

Offline RL Q-Learning +1

Unsupervised Sentiment Analysis by Transferring Multi-source Knowledge

no code implementations9 May 2021 Yong Dai, Jian Liu, Jian Zhang, Hongguang Fu, Zenglin Xu

The first mechanism is a selective domain adaptation (SDA) method, which transfers knowledge from the closest source domain.

Domain Adaptation Sentiment Analysis

Underwater Target Recognition based on Multi-Decision LOFAR Spectrum Enhancement: A Deep Learning Approach

no code implementations26 Apr 2021 Jie Chen, Jie Liu, Chang Liu, Jian Zhang, Bing Han

To overcome this issue and to further improve the recognition performance, we adopt a deep learning approach for underwater target recognition and propose a LOFAR spectrum enhancement (LSE)-based underwater target recognition scheme, which consists of preprocessing, offline training, and online testing.

Super-Resolving Compressed Video in Coding Chain

no code implementations26 Mar 2021 Dewang Hou, Yang Zhao, Yuyao Ye, Jiayu Yang, Jian Zhang, Ronggang Wang

Scaling and lossy coding are widely used in video transmission and storage.

Jo-SRC: A Contrastive Approach for Combating Noisy Labels

1 code implementation CVPR 2021 Yazhou Yao, Zeren Sun, Chuanyi Zhang, Fumin Shen, Qi Wu, Jian Zhang, Zhenmin Tang

Due to the memorization effect in Deep Neural Networks (DNNs), training with noisy labels usually results in inferior model performance.

Contrastive Learning

ISTA-Net++: Flexible Deep Unfolding Network for Compressive Sensing

1 code implementation22 Mar 2021 Di You, Jingfen Xie, Jian Zhang

While deep neural networks have achieved impressive success in image compressive sensing (CS), most of them lack flexibility when dealing with multi-ratio tasks and multi-scene images in practical applications.

Compressive Sensing

Thousand to One: Semantic Prior Modeling for Conceptual Coding

no code implementations12 Mar 2021 Jianhui Chang, Zhenghui Zhao, Lingbo Yang, Chuanmin Jia, Jian Zhang, Siwei Ma

To this end, we propose a novel end-to-end semantic prior modeling-based conceptual coding scheme towards extremely low bitrate image compression, which leverages semantic-wise deep representations as a unified prior for entropy estimation and texture synthesis.

Image Compression Semantic Segmentation +1

COLA-Net: Collaborative Attention Network for Image Restoration

2 code implementations10 Mar 2021 Chong Mou, Jian Zhang, Xiaopeng Fan, Hangfan Liu, Ronggang Wang

Local and non-local attention-based methods have been well studied in various image restoration tasks while leading to promising performance.

Image Denoising Image Restoration

A comprehensive survey on point cloud registration

no code implementations3 Mar 2021 Xiaoshui Huang, Guofeng Mei, Jian Zhang, Rana Abbas

This survey conducts a comprehensive survey, including both same-source and cross-source registration methods, and summarize the connections between optimization-based and deep learning methods, to provide further research insight.

3D Reconstruction Point Cloud Registration

Temperature dependent coherence properties of NV ensemble in diamond up to 600K

no code implementations25 Feb 2021 Shengran Lin, Changfeng Weng, Yuanjie Yang, Jiaxin Zhao, Yuhang Guo, Jian Zhang, Liren Lou, Wei Zhu, Guanzhong Wang

Nitrogen-vacancy (NV) center in diamond is an ideal candidate for quantum sensors because of its excellent optical and coherence property.

Quantum Physics Mesoscale and Nanoscale Physics

Temporal-Amount Snapshot MultiGraph for Ethereum Transaction Tracking

no code implementations16 Feb 2021 Yunyi Xie, Jie Jin, Jian Zhang, Shanqing Yu, Qi Xuan

With the wide application of blockchain in the financial field, the rise of various types of cybercrimes has brought great challenges to the security of blockchain.

Link Prediction

Exploiting Web Images for Fine-Grained Visual Recognition by Eliminating Noisy Samples and Utilizing Hard Ones

1 code implementation23 Jan 2021 Huafeng Liu, Chuanyi Zhang, Yazhou Yao, Xiushen Wei, Fumin Shen, Jian Zhang, Zhenmin Tang

Labeling objects at a subordinate level typically requires expert knowledge, which is not always available when using random annotators.

Fine-Grained Visual Recognition

Super Resolve Dynamic Scene From Continuous Spike Streams

no code implementations ICCV 2021 Jing Zhao, Jiyu Xie, Ruiqin Xiong, Jian Zhang, Zhaofei Yu, Tiejun Huang

In this paper, we properly exploit the relative motion and derive the relationship between light intensity and each spike, so as to recover the external scene with both high temporal and high spatial resolution.


Uncertainty Weighted Offline Reinforcement Learning

no code implementations1 Jan 2021 Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh

Offline Reinforcement Learning promises to learn effective policies from previously-collected, static datasets without the need for exploration.

Offline RL Q-Learning +1

Revisiting BFfloat16 Training

no code implementations1 Jan 2021 Pedram Zamirai, Jian Zhang, Christopher R Aberger, Christopher De Sa

We ask can we do pure 16-bit training which requires only 16-bit compute units, while still matching the model accuracy attained by 32-bit training.

Multi-Representation Ensemble in Few-Shot Learning

no code implementations1 Jan 2021 Qing Chen, Jian Zhang

Deep neural networks (DNNs) compute representations in a layer by layer fashion, producing a final representation at the top layer of the pipeline, and classification or regression is made using the final representation.

Few-Shot Learning

Counting the Number of Solutions to Constraints

no code implementations28 Dec 2020 Jian Zhang, Cunjing Ge, Feifei Ma

Compared with constraint satisfaction problems, counting problems have received less attention.

Multiple Instance Segmentation in Brachial Plexus Ultrasound Image Using BPMSegNet

no code implementations22 Dec 2020 Yi Ding, Qiqi Yang, Guozheng Wu, Jian Zhang, Zhiguang Qin

In this paper, a network called Brachial Plexus Multi-instance Segmentation Network (BPMSegNet) is proposed to identify different tissues (nerves, arteries, veins, muscles) in ultrasound images.

Instance Segmentation Semantic Segmentation

PTN: A Poisson Transfer Network for Semi-supervised Few-shot Learning

no code implementations20 Dec 2020 Huaxi Huang, Junjie Zhang, Jian Zhang, Qiang Wu, Chang Xu

Second, the extra unlabeled samples are employed to transfer the knowledge from base classes to novel classes through contrastive learning.

Contrastive Learning Few-Shot Learning

Self-Supervised Learning of Lidar Segmentation for Autonomous Indoor Navigation

no code implementations10 Dec 2020 Hugues Thomas, Ben Agro, Mona Gridseth, Jian Zhang, Timothy D. Barfoot

We provide insights into our network predictions and show that our approach can also improve the performances of common localization techniques.

Point Cloud Segmentation Self-Supervised Learning +2

Rigid and Articulated Point Registration with Expectation Conditional Maximization

no code implementations9 Dec 2020 Radu Horaud, Florence Forbes, Manuel Yguel, Guillaume Dewaele, Jian Zhang

This paper addresses the issue of matching rigid and articulated shapes through probabilistic point registration.

Field-wise Learning for Multi-field Categorical Data

1 code implementation NeurIPS 2020 Zhibin Li, Jian Zhang, Yongshun Gong, Yazhou Yao, Qiang Wu

We present a model that utilizes linear models with variance and low-rank constraints, to help it generalize better and reduce the number of parameters.

Time-Series Snapshot Network for Partner Recommendation: A Case Study on OSS

no code implementations18 Nov 2020 Jinyin Chen, Yunyi Xie, Jian Zhang, Xincheng Shu, Qi Xuan

In this paper, we introduce time-series snapshot network (TSSN) which is a mixture network to model the interactions among users and developers.

Social and Information Networks

Conceptual Compression via Deep Structure and Texture Synthesis

2 code implementations10 Nov 2020 Jianhui Chang, Zhenghui Zhao, Chuanmin Jia, Shiqi Wang, Lingbo Yang, Qi Mao, Jian Zhang, Siwei Ma

To this end, we propose a novel conceptual compression framework that encodes visual data into compact structure and texture representations, then decodes in a deep synthesis fashion, aiming to achieve better visual reconstruction quality, flexible content manipulation, and potential support for various vision tasks.

Texture Synthesis

Multi-layer Feature Aggregation for Deep Scene Parsing Models

no code implementations4 Nov 2020 Litao Yu, Yongsheng Gao, Jun Zhou, Jian Zhang, Qiang Wu

The proposed module can auto-select the intermediate visual features to correlate the spatial and semantic information.

Scene Parsing Semantic Segmentation

Parameter Efficient Deep Neural Networks with Bilinear Projections

1 code implementation3 Nov 2020 Litao Yu, Yongsheng Gao, Jun Zhou, Jian Zhang

Recent research on deep neural networks (DNNs) has primarily focused on improving the model accuracy.

Distribution-aware Margin Calibration for Medical Image Segmentation

no code implementations3 Nov 2020 Zhibin Li, Litao Yu, Jian Zhang

In this paper, we present a novel data-distribution-aware margin calibration method for a better generalization of the mIoU over the whole data-distribution, underpinned by a rigid lower bound.

Medical Image Segmentation Semantic Segmentation

Dual Attention on Pyramid Feature Maps for Image Captioning

no code implementations2 Nov 2020 Litao Yu, Jian Zhang, Qiang Wu

In this paper, we propose to apply dual attention on pyramid image feature maps to fully explore the visual-semantic correlations and improve the quality of generated sentences.

Image Captioning

Identification of deep breath while moving forward based on multiple body regions and graph signal analysis

no code implementations20 Oct 2020 Yunlu Wang, Cheng Yang, Menghan Hu, Jian Zhang, Qingli Li, Guangtao Zhai, Xiao-Ping Zhang

This paper presents an unobtrusive solution that can automatically identify deep breath when a person is walking past the global depth camera.

AutoBSS: An Efficient Algorithm for Block Stacking Style Search

no code implementations NeurIPS 2020 Yikang Zhang, Jian Zhang, Zhao Zhong

Neural network architecture design mostly focuses on the new convolutional operator or special topological structure of network block, little attention is drawn to the configuration of stacking each block, called Block Stacking Style (BSS).

AutoML Instance Segmentation +3

Revisiting BFloat16 Training

no code implementations13 Oct 2020 Pedram Zamirai, Jian Zhang, Christopher R. Aberger, Christopher De Sa

State-of-the-art generic low-precision training algorithms use a mix of 16-bit and 32-bit precision, creating the folklore that 16-bit hardware compute units alone are not enough to maximize model accuracy.

Face Mask Assistant: Detection of Face Mask Service Stage Based on Mobile Phone

no code implementations9 Oct 2020 Yuzhen Chen, Menghan Hu, Chunjun Hua, Guangtao Zhai, Jian Zhang, Qingli Li, Simon X. Yang

Aimed at solving the problem that we don't know which service stage of the mask belongs to, we propose a detection system based on the mobile phone.

ASDN: A Deep Convolutional Network for Arbitrary Scale Image Super-Resolution

1 code implementation6 Oct 2020 Jialiang Shen, Yucheng Wang, Jian Zhang

For SR of small-scales (between 1 and 2), images are constructed by interpolation from a sparse set of precalculated Laplacian pyramid levels.

Image Super-Resolution

Scalar Coupling Constant Prediction Using Graph Embedding Local Attention Encoder

no code implementations7 Sep 2020 Caiqing Jian, Xinyu Cheng, Jian Zhang, Lihui Wang

The experimental results demonstrate that, compared to the traditional chemical bond structure representations, the rotation and translation invariant structure representations proposed in this work can improve the SCC prediction accuracy; with the graph embedded local self-attention, the mean absolute error (MAE) of the prediction model in the validation set decreases from 0. 1603 Hz to 0. 1067 Hz; using the classification based loss function instead of the scaled regression loss, the MAE of the predicted SCC can be decreased to 0. 0963 HZ, which is close to the quantum chemistry standard on CHAMPS dataset.

Graph Embedding

Implicit Multidimensional Projection of Local Subspaces

1 code implementation7 Sep 2020 Rongzheng Bian, Yumeng Xue, Liang Zhou, Jian Zhang, Baoquan Chen, Daniel Weiskopf, Yunhai Wang

We propose a visualization method to understand the effect of multidimensional projection on local subspaces, using implicit function differentiation.

Salvage Reusable Samples from Noisy Data for Robust Learning

1 code implementation6 Aug 2020 Zeren Sun, Xian-Sheng Hua, Yazhou Yao, Xiu-Shen Wei, Guosheng Hu, Jian Zhang

To this end, we propose a certainty-based reusable sample selection and correction approach, termed as CRSSC, for coping with label noise in training deep FG models with web images.

Hardware Accelerator for Adversarial Attacks on Deep Learning Neural Networks

no code implementations3 Aug 2020 Haoqiang Guo, Lu Peng, Jian Zhang, Fang Qi, Lide Duan

Recent studies identify that Deep learning Neural Networks (DNNs) are vulnerable to subtle perturbations, which are not perceptible to human visual system but can fool the DNN models and lead to wrong outputs.

Adversarial Attack

MACD R-CNN: An Abnormal Cell Nucleus Detection Method

no code implementations28 Jul 2020 Baoyan Ma, Jian Zhang, Feng Cao, Yongjun He

We design a fixed proposal module to generate fixed-sized feature maps of nuclei, which allows the new information of nucleus is used for classification.

Classification General Classification +3

A Similarity Inference Metric for RGB-Infrared Cross-Modality Person Re-identification

no code implementations3 Jul 2020 Mengxi Jia, Yunpeng Zhai, Shijian Lu, Siwei Ma, Jian Zhang

RGB-Infrared (IR) cross-modality person re-identification (re-ID), which aims to search an IR image in RGB gallery or vice versa, is a challenging task due to the large discrepancy between IR and RGB modalities.

Cross-Modality Person Re-identification Person Re-Identification

Stochastic Batch Augmentation with An Effective Distilled Dynamic Soft Label Regularizer

no code implementations27 Jun 2020 Qian Li, Qingyuan Hu, Yong Qi, Saiyu Qi, Jie Ma, Jian Zhang

SBA stochastically decides whether to augment at iterations controlled by the batch scheduler and in which a ''distilled'' dynamic soft label regularization is introduced by incorporating the similarity in the vicinity distribution respect to raw samples.

Data Augmentation

Understanding Graph Neural Networks from Graph Signal Denoising Perspectives

1 code implementation8 Jun 2020 Guoji Fu, Yifan Hou, Jian Zhang, Kaili Ma, Barakeel Fanseu Kamhoua, James Cheng

This paper aims to provide a theoretical framework to understand GNNs, specifically, spectral graph convolutional networks and graph attention networks, from graph signal denoising perspectives.

Denoising Graph Attention +2

TOAN: Target-Oriented Alignment Network for Fine-Grained Image Categorization with Few Labeled Samples

no code implementations28 May 2020 Huaxi Huang, Jun-Jie Zhang, Jian Zhang, Qiang Wu, Chang Xu

The challenges of high intra-class variance yet low inter-class fluctuations in fine-grained visual categorization are more severe with few labeled samples, \textit{i. e.,} Fine-Grained categorization problems under the Few-Shot setting (FGFS).

Fine-Grained Visual Categorization

Iterative Network for Image Super-Resolution

1 code implementation20 May 2020 Yuqing Liu, Shiqi Wang, Jian Zhang, Shanshe Wang, Siwei Ma, Wen Gao

A novel iterative super-resolution network (ISRN) is proposed on top of the iterative optimization.

Image Super-Resolution SSIM

Contextual Embeddings: When Are They Worth It?

no code implementations ACL 2020 Simran Arora, Avner May, Jian Zhang, Christopher Ré

We study the settings for which deep contextual embeddings (e. g., BERT) give large improvements in performance relative to classic pretrained embeddings (e. g., GloVe), and an even simpler baseline---random word embeddings---focusing on the impact of the training set size and the linguistic properties of the task.

Word Embeddings

Towards Better Graph Representation: Two-Branch Collaborative Graph Neural Networks for Multimodal Marketing Intention Detection

no code implementations13 May 2020 Lu Zhang, Jian Zhang, Zhibin Li, Jingsong Xu

Inspired by the fact that spreading and collecting information through the Internet becomes the norm, more and more people choose to post for-profit contents (images and texts) in social networks.

Graph Classification

Feature-metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud Registration without Correspondences

1 code implementation CVPR 2020 Xiaoshui Huang, Guofeng Mei, Jian Zhang

We present a fast feature-metric point cloud registration framework, which enforces the optimisation of registration by minimising a feature-metric projection error without correspondences.

Point Cloud Registration

DyNet: Dynamic Convolution for Accelerating Convolutional Neural Networks

no code implementations22 Apr 2020 Yikang Zhang, Jian Zhang, Qiang Wang, Zhao Zhong

On one hand, we can reduce the computation cost remarkably while maintaining the performance.

GID-Net: Detecting Human-Object Interaction with Global and Instance Dependency

no code implementations11 Mar 2020 Dongming Yang, Yuexian Zou, Jian Zhang, Ge Li

GID block breaks through the local neighborhoods and captures long-range dependency of pixels both in global-level and instance-level from the scene to help detecting interactions between instances.

Human-Object Interaction Detection

Understanding the Downstream Instability of Word Embeddings

1 code implementation29 Feb 2020 Megan Leszczynski, Avner May, Jian Zhang, Sen Wu, Christopher R. Aberger, Christopher Ré

To theoretically explain this tradeoff, we introduce a new measure of embedding instability---the eigenspace instability measure---which we prove bounds the disagreement in downstream predictions introduced by the change in word embeddings.

Word Embeddings

Multi-factorial Optimization for Large-scale Virtual Machine Placement in Cloud Computing

no code implementations18 Jan 2020 Zhengping Liang, Jian Zhang, Liang Feng, Zexuan Zhu

However, as growing demand for cloud services, the existing EAs fail to implement in large-scale virtual machine placement (LVMP) problem due to the high time complexity and poor scalability.

PMC-GANs: Generating Multi-Scale High-Quality Pedestrian with Multimodal Cascaded GANs

no code implementations30 Dec 2019 Jie Wu, Ying Peng, Chenghao Zheng, Zongbo Hao, Jian Zhang

Recently, generative adversarial networks (GANs) have shown great advantages in synthesizing images, leading to a boost of explorations of using faked images to augment data.

Data Augmentation Pedestrian Detection

Adversarial AutoAugment

no code implementations ICLR 2020 Xin-Yu Zhang, Qiang Wang, Jian Zhang, Zhao Zhong

The augmentation policy network attempts to increase the training loss of a target network through generating adversarial augmentation policies, while the target network can learn more robust features from harder examples to improve the generalization.

Data Augmentation Image Classification

Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development

no code implementations7 Dec 2019 Yongshun Gong, Zhibin Li, Jian Zhang, Wei Liu, Jin-Feng Yi

In this paper, this specific problem is termed as potential passenger flow (PPF) prediction, which is a novel and important study connected with urban computing and intelligent transportation systems.

MULTI-VIEW LEARNING Recommendation Systems

Adversarial Domain Adaptation with Domain Mixup

1 code implementation4 Dec 2019 Minghao Xu, Jian Zhang, Bingbing Ni, Teng Li, Chengjie Wang, Qi Tian, Wenjun Zhang

In this paper, we present adversarial domain adaptation with domain mixup (DM-ADA), which guarantees domain-invariance in a more continuous latent space and guides the domain discriminator in judging samples' difference relative to source and target domains.

Domain Adaptation

Time-aware Gradient Attack on Dynamic Network Link Prediction

no code implementations24 Nov 2019 Jinyin Chen, Jian Zhang, Zhi Chen, Min Du, Qi Xuan

In this work, we present the first study of adversarial attack on dynamic network link prediction (DNLP).

Adversarial Attack Link Prediction +1

Worst Cases Policy Gradients

1 code implementation9 Nov 2019 Yichuan Charlie Tang, Jian Zhang, Ruslan Salakhutdinov

Recent advances in deep reinforcement learning have demonstrated the capability of learning complex control policies from many types of environments.


Max-min Fairness of K-user Cooperative Rate-Splitting in MISO Broadcast Channel with User Relaying

no code implementations17 Oct 2019 Yijie Mao, Bruno Clerckx, Jian Zhang, Victor O. K. Li, Mohammed Arafah

Cooperative Rate-Splitting (CRS) strategy, relying on linearly precoded rate-splitting at the transmitter and opportunistic transmission of the common message by the relaying user, has recently been shown to outperform typical Non-cooperative Rate-Splitting (NRS), Cooperative Non-Orthogonal Multiple Access (C-NOMA) and Space Division Multiple Access (SDMA) in a two-user Multiple Input Single Output (MISO) Broadcast Channel (BC) with user relaying.


PipeMare: Asynchronous Pipeline Parallel DNN Training

no code implementations9 Oct 2019 Bowen Yang, Jian Zhang, Jonathan Li, Christopher Ré, Christopher R. Aberger, Christopher De Sa

Pipeline parallelism (PP) when training neural networks enables larger models to be partitioned spatially, leading to both lower network communication and overall higher hardware utilization.

DyNet: Dynamic Convolution for Accelerating Convolution Neural Networks

no code implementations25 Sep 2019 Kane Zhang, Jian Zhang, Qiang Wang, Zhao Zhong

To verify the scalability, we also apply DyNet on segmentation task, the results show that DyNet can reduces 69. 3% FLOPs while maintaining the Mean IoU on segmentation task.

On the Downstream Performance of Compressed Word Embeddings

1 code implementation NeurIPS 2019 Avner May, Jian Zhang, Tri Dao, Christopher Ré

Finally, we show that by using the eigenspace overlap score as a selection criterion between embeddings drawn from a representative set we compressed, we can efficiently identify the better performing embedding with up to $2\times$ lower selection error rates than the next best measure of compression quality, and avoid the cost of training a model for each task of interest.

Generalization Bounds Quantization +1

C-RPNs: Promoting Object Detection in real world via a Cascade Structure of Region Proposal Networks

no code implementations19 Aug 2019 Dongming Yang, Yuexian Zou, Jian Zhang, Ge Li

Although two-stage detectors like Faster R-CNN achieved big successes in object detection due to the strategy of extracting region proposals by region proposal network, they show their poor adaption in real-world object detection as a result of without considering mining hard samples during extracting region proposals.

Object Detection Region Proposal

Exploiting Channel Similarity for Accelerating Deep Convolutional Neural Networks

no code implementations6 Aug 2019 Yunxiang Zhang, Chenglong Zhao, Bingbing Ni, Jian Zhang, Haoran Deng

To address the limitations of existing magnitude-based pruning algorithms in cases where model weights or activations are of large and similar magnitude, we propose a novel perspective to discover parameter redundancy among channels and accelerate deep CNNs via channel pruning.

Low-Rank Pairwise Alignment Bilinear Network For Few-Shot Fine-Grained Image Classification

no code implementations4 Aug 2019 Huaxi Huang, Jun-Jie Zhang, Jian Zhang, Jingsong Xu, Qiang Wu

A novel low-rank pairwise bilinear pooling operation is proposed to capture the nuanced differences between the support and query images for learning an effective distance metric.

Classification Few-Shot Learning +2

Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points

no code implementations2 Jul 2019 Zhibin Li, Jian Zhang, Qiang Wu, Yongshun Gong, Jin-Feng Yi, Christina Kirsch

In this paper, we formulate our prediction task as a multiple kernel learning problem with missing kernels.

Extracting Visual Knowledge from the Internet: Making Sense of Image Data

no code implementations7 Jun 2019 Yazhou Yao, Jian Zhang, Xian-Sheng Hua, Fumin Shen, Zhenmin Tang

Recent successes in visual recognition can be primarily attributed to feature representation, learning algorithms, and the ever-increasing size of labeled training data.

Representation Learning

Glioma Grade Prediction Using Wavelet Scattering-Based Radiomics

no code implementations23 May 2019 Qijian Chen, Lihui Wang, Li Wang, Zeyu Deng, Jian Zhang, Yuemin Zhu

Glioma grading before surgery is very critical for the prognosis prediction and treatment plan making.

Dimensionality Reduction

Structured Discriminative Tensor Dictionary Learning for Unsupervised Domain Adaptation

no code implementations11 May 2019 Songsong Wu, Yan Yan, Hao Tang, Jianjun Qian, Jian Zhang, Xiao-Yuan Jing

However, the number of labeled source samples are always limited due to expensive annotation cost in practice, making sub-optimal performance been observed.

Dictionary Learning Unsupervised Domain Adaptation

Inferring the Importance of Product Appearance: A Step Towards the Screenless Revolution

no code implementations1 May 2019 Yongshun Gong, Jin-Feng Yi, Dong-Dong Chen, Jian Zhang, Jiayu Zhou, Zhihua Zhou

In this paper, we aim to infer the significance of every item's appearance in consumer decision making and identify the group of items that are suitable for screenless shopping.

Decision Making

Low-Memory Neural Network Training: A Technical Report

no code implementations24 Apr 2019 Nimit S. Sohoni, Christopher R. Aberger, Megan Leszczynski, Jian Zhang, Christopher Ré

In this paper we study a fundamental question: How much memory is actually needed to train a neural network?

14 Image Classification +2

Local Deep-Feature Alignment for Unsupervised Dimension Reduction

no code implementations22 Apr 2019 Jian Zhang, Jun Yu, DaCheng Tao

Next, we exploit an affine transformation to align the local deep features of each neighbourhood with the global features.

Data Visualization Dimensionality Reduction

Single Pixel Reconstruction for One-stage Instance Segmentation

no code implementations16 Apr 2019 Jun Yu, Jinghan Yao, Jian Zhang, Zhou Yu, DaCheng Tao

In this paper, we propose a one-stage framework, SPRNet, which performs efficient instance segmentation by introducing a single pixel reconstruction (SPR) branch to off-the-shelf one-stage detectors.

Instance Segmentation Region Proposal +1

Compare More Nuanced:Pairwise Alignment Bilinear Network For Few-shot Fine-grained Learning

no code implementations7 Apr 2019 Huaxi Huang, Jun-Jie Zhang, Jian Zhang, Qiang Wu, Jingsong Xu

Unlike traditional deep bilinear networks for fine-grained classification, which adopt the self-bilinear pooling to capture the subtle features of images, the proposed model uses a novel pairwise bilinear pooling to compare the nuanced differences between base images and query images for learning a deep distance metric.

General Classification Meta-Learning

Towards Locally Consistent Object Counting with Constrained Multi-stage Convolutional Neural Networks

no code implementations6 Apr 2019 Muming Zhao, Jian Zhang, Chongyang Zhang, Wenjun Zhang

Towards this problem, in this paper we propose a constrained multi-stage Convolutional Neural Networks (CNNs) to jointly pursue locally consistent density map from two aspects.

Object Counting

Fast Registration for cross-source point clouds by using weak regional affinity and pixel-wise refinement

no code implementations11 Mar 2019 Xiaoshui Huang, Lixin Fan, Qiang Wu, Jian Zhang, Chun Yuan

Accurate and fast registration of cross-source 3D point clouds from different sensors is an emerged research problem in computer vision.

Point Cloud Registration

Unsupervised Part Mining for Fine-grained Image Classification

no code implementations26 Feb 2019 Runsheng Zhang, Jian Zhang, Yaping Huang, Qi Zou

To tackle this issue, we propose a fully unsupervised part mining (UPM) approach to localize the discriminative parts without even image-level annotations, which largely improves the fine-grained classification performance.

Classification Fine-Grained Image Classification +1

Object Discovery From a Single Unlabeled Image by Mining Frequent Itemset With Multi-scale Features

1 code implementation26 Feb 2019 Runsheng Zhang, Yaping Huang, Mengyang Pu, Jian Zhang, Qingji Guan, Qi Zou, Haibin Ling

To tackle this problem, we propose a simple but effective pattern mining-based method, called Object Location Mining (OLM), which exploits the advantages of data mining and feature representation of pre-trained convolutional neural networks (CNNs).

Object Discovery Saliency Detection +1

Learning Extreme Hummingbird Maneuvers on Flapping Wing Robots

no code implementations25 Feb 2019 Fan Fei, Zhan Tu, Jian Zhang, Xinyan Deng

Inspired by the hummingbirds' near-maximal performance during such extreme maneuvers, we developed a flight control strategy and experimentally demonstrated that such maneuverability can be achieved by an at-scale 12-gram hummingbird robot equipped with just two actuators.


Flappy Hummingbird: An Open Source Dynamic Simulation of Flapping Wing Robots and Animals

1 code implementation25 Feb 2019 Fan Fei, Zhan Tu, Yilun Yang, Jian Zhang, Xinyan Deng

Here, we present an open source high fidelity dynamic simulation for FWMAVs to serve as a testbed for the design, optimization and flight control of FWMAVs.

OpenAI Gym reinforcement-learning

E-LSTM-D: A Deep Learning Framework for Dynamic Network Link Prediction

1 code implementation22 Feb 2019 Jinyin Chen, Jian Zhang, Xuanheng Xu, Chengbo Fu, Dan Zhang, Qingpeng Zhang, Qi Xuan

Predicting the potential relations between nodes in networks, known as link prediction, has long been a challenge in network science.

Link Prediction Time Series

Assessment of central serous chorioretinopathy (CSC) depicted on color fundus photographs using deep Learning

no code implementations14 Jan 2019 Yi Zhen, Hang Chen, Xu Zhang, Meng Liu, Xin Meng, Jian Zhang, Jiantao Pu

To investigate whether and to what extent central serous chorioretinopathy (CSC) depicted on color fundus photographs can be assessed using deep learning technology.

Low-Precision Random Fourier Features for Memory-Constrained Kernel Approximation

1 code implementation31 Oct 2018 Jian Zhang, Avner May, Tri Dao, Christopher Ré

We investigate how to train kernel approximation methods that generalize well under a memory budget.


Performance assessment of the deep learning technologies in grading glaucoma severity

no code implementations31 Oct 2018 Yi Zhen, Lei Wang, Han Liu, Jian Zhang, Jiantao Pu

Among these CNNs, the DenseNet had the highest classification accuracy (i. e., 75. 50%) based on pre-trained weights when using global ROIs, as compared to 65. 50% when using local ROIs.

Deep Bi-Dense Networks for Image Super-Resolution

1 code implementation11 Oct 2018 Yucheng Wang, Jialiang Shen, Jian Zhang

In this way, feature information propagates from a single dense block to all subsequent blocks, instead of to a single successor.

Image Super-Resolution

Scene Text Recognition from Two-Dimensional Perspective

no code implementations18 Sep 2018 Minghui Liao, Jian Zhang, Zhaoyi Wan, Fengming Xie, Jiajun Liang, Pengyuan Lyu, Cong Yao, Xiang Bai

Inspired by speech recognition, recent state-of-the-art algorithms mostly consider scene text recognition as a sequence prediction problem.

Scene Text Recognition Semantic Segmentation +1

Goal-Oriented Visual Question Generation via Intermediate Rewards

no code implementations ECCV 2018 Jun-Jie Zhang, Qi Wu, Chunhua Shen, Jian Zhang, Jianfeng Lu, Anton Van Den Hengel

Despite significant progress in a variety of vision-and-language problems, developing a method capable of asking intelligent, goal-oriented questions about images is proven to be an inscrutable challenge.

Informativeness Question Generation +1

Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark

no code implementations4 Jun 2018 Cody Coleman, Daniel Kang, Deepak Narayanan, Luigi Nardi, Tian Zhao, Jian Zhang, Peter Bailis, Kunle Olukotun, Chris Re, Matei Zaharia

In this work, we analyze the entries from DAWNBench, which received optimized submissions from multiple industrial groups, to investigate the behavior of TTA as a metric as well as trends in the best-performing entries.

Fine-Grained Video Captioning for Sports Narrative

no code implementations CVPR 2018 Huanyu Yu, Shuo Cheng, Bingbing Ni, Minsi Wang, Jian Zhang, Xiaokang Yang

First, to facilitate this novel research of fine-grained video caption, we collected a novel dataset called Fine-grained Sports Narrative dataset (FSN) that contains 2K sports videos with ground-truth narratives from YouTube. com.

Video Captioning

Feature Affinity based Pseudo Labeling for Semi-supervised Person Re-identification

no code implementations16 May 2018 Guodong Ding, Shanshan Zhang, Salman Khan, Zhenmin Tang, Jian Zhang, Fatih Porikli

Our approach measures the affinity of unlabeled samples with the underlying clusters of labeled data samples using the intermediate feature representations from deep networks.

Data Augmentation Representation Learning +1

High-Accuracy Low-Precision Training

1 code implementation9 Mar 2018 Christopher De Sa, Megan Leszczynski, Jian Zhang, Alana Marzoev, Christopher R. Aberger, Kunle Olukotun, Christopher Ré

Low-precision computation is often used to lower the time and energy cost of machine learning, and recently hardware accelerators have been developed to support it.


Structured Control Nets for Deep Reinforcement Learning

1 code implementation ICML 2018 Mario Srouji, Jian Zhang, Ruslan Salakhutdinov

The proposed Structured Control Net (SCN) splits the generic MLP into two separate sub-modules: a nonlinear control module and a linear control module.

Decision Making reinforcement-learning

Deep Reinforcement Learning for Image Hashing

no code implementations7 Feb 2018 Yuxin Peng, Jian Zhang, Zhaoda Ye

Inspired by the sequential decision ability of deep reinforcement learning, we propose a new Deep Reinforcement Learning approach for Image Hashing (DRLIH).


SCH-GAN: Semi-supervised Cross-modal Hashing by Generative Adversarial Network

no code implementations7 Feb 2018 Jian Zhang, Yuxin Peng, Mingkuan Yuan

(2) Ignore the rich information contained in the large amount of unlabeled data across different modalities, especially the margin examples that are easily to be incorrectly retrieved, which can help to model the correlations.

Multi-pseudo Regularized Label for Generated Data in Person Re-Identification

no code implementations21 Jan 2018 Yan Huang, Jinsong Xu, Qiang Wu, Zhedong Zheng, Zhao-Xiang Zhang, Jian Zhang

Unlike the traditional label which usually is a single integral number, the virtual label proposed in this work is a set of weight-based values each individual of which is a number in (0, 1] called multi-pseudo label and reflects the degree of relation between each generated data to every pre-defined class of real data.

Person Re-Identification

Unsupervised Generative Adversarial Cross-modal Hashing

no code implementations1 Dec 2017 Jian Zhang, Yuxin Peng, Mingkuan Yuan

To address the above problem, in this paper we propose an Unsupervised Generative Adversarial Cross-modal Hashing approach (UGACH), which makes full use of GAN's ability for unsupervised representation learning to exploit the underlying manifold structure of cross-modal data.

Cross-Modal Retrieval Representation Learning

Asking the Difficult Questions: Goal-Oriented Visual Question Generation via Intermediate Rewards

no code implementations21 Nov 2017 Jun-Jie Zhang, Qi Wu, Chunhua Shen, Jian Zhang, Jianfeng Lu, Anton Van Den Hengel

Despite significant progress in a variety of vision-and-language problems, developing a method capable of asking intelligent, goal-oriented questions about images is proven to be an inscrutable challenge.

Informativeness Question Generation +1

Kill Two Birds with One Stone: Weakly-Supervised Neural Network for Image Annotation and Tag Refinement

no code implementations19 Nov 2017 Jun-Jie Zhang, Qi Wu, Jian Zhang, Chunhua Shen, Jianfeng Lu

These comments can be a description of the image, or some objects, attributes, scenes in it, which are normally used as the user-provided tags.


Natural Language Inference over Interaction Space

2 code implementations ICLR 2018 Yichen Gong, Heng Luo, Jian Zhang

Natural Language Inference (NLI) task requires an agent to determine the logical relationship between a natural language premise and a natural language hypothesis.

Natural Language Inference Paraphrase Identification

Towards Automatic Construction of Diverse, High-quality Image Dataset

no code implementations22 Aug 2017 Yazhou Yao, Jian Zhang, Fumin Shen, Li Liu, Fan Zhu, Dongxiang Zhang, Heng-Tao Shen

To eliminate manual annotation, in this work, we propose a novel image dataset construction framework by employing multiple textual queries.

Image Classification Object Detection

ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing

1 code implementation CVPR 2018 Jian Zhang, Bernard Ghanem

With the aim of developing a fast yet accurate algorithm for compressive sensing (CS) reconstruction of natural images, we combine in this paper the merits of two existing categories of CS methods: the structure insights of traditional optimization-based methods and the speed of recent network-based ones.

Compressive Sensing

Place recognition: An Overview of Vision Perspective

no code implementations17 Jun 2017 Zhiqiang Zeng, Jian Zhang, Xiaodong Wang, Yuming Chen, Chaoyang Zhu

Place recognition is one of the most fundamental topics in computer vision and robotics communities, where the task is to accurately and efficiently recognize the location of a given query image.

Image Classification Image Retrieval +2

A New Probabilistic Algorithm for Approximate Model Counting

no code implementations13 Jun 2017 Cunjing Ge, Feifei Ma, Tian Liu, Jian Zhang

Constrained counting is important in domains ranging from artificial intelligence to software analysis.

YellowFin and the Art of Momentum Tuning

2 code implementations ICLR 2018 Jian Zhang, Ioannis Mitliagkas

We revisit the momentum SGD algorithm and show that hand-tuning a single learning rate and momentum makes it competitive with Adam.

Constituency Parsing Language Modelling

Refining Image Categorization by Exploiting Web Images and General Corpus

no code implementations16 Mar 2017 Yazhou Yao, Jian Zhang, Fumin Shen, Xian-Sheng Hua, Wankou Yang, Zhenmin Tang

To tackle these problems, in this work, we exploit general corpus information to automatically select and subsequently classify web images into semantic rich (sub-)categories.

Image Categorization

Query-adaptive Image Retrieval by Deep Weighted Hashing

no code implementations8 Dec 2016 Jian Zhang, Yuxin Peng

On the other hand, different hash bits actually contribute to the image retrieval differently, and treating them equally greatly affects the retrieval accuracy of image.

Image Retrieval

Multi-Label Image Classification with Regional Latent Semantic Dependencies

no code implementations4 Dec 2016 Jun-Jie Zhang, Qi Wu, Chunhua Shen, Jian Zhang, Jianfeng Lu

Recent state-of-the-art approaches to multi-label image classification exploit the label dependencies in an image, at global level, largely improving the labeling capacity.

Classification General Classification +1

Fast Gated Neural Domain Adaptation: Language Model as a Case Study

no code implementations COLING 2016 Jian Zhang, Xiaofeng Wu, Andy Way, Qun Liu

We show that the neural LM perplexity can be reduced by 7. 395 and 12. 011 using the proposed domain adaptation mechanism on the Penn Treebank and News data, respectively.

Domain Adaptation Language Modelling +2

Topic-Informed Neural Machine Translation

no code implementations COLING 2016 Jian Zhang, Liangyou Li, Andy Way, Qun Liu

In recent years, neural machine translation (NMT) has demonstrated state-of-the-art machine translation (MT) performance.

Machine Translation Topic Models +1

Exploiting Web Images for Dataset Construction: A Domain Robust Approach

no code implementations22 Nov 2016 Yazhou Yao, Jian Zhang, Fumin Shen, Xian-Sheng Hua, Jingsong Xu, Zhenmin Tang

To reduce the cost of manual labelling, there has been increased research interest in automatically constructing image datasets by exploiting web images.

Domain Adaptation Image Classification +1

A coarse-to-fine algorithm for registration in 3D street-view cross-source point clouds

no code implementations24 Oct 2016 Xiaoshui Huang, Jian Zhang, Qiang Wu, Lixin Fan, Chun Yuan

In this paper, different from previous ICP-based methods, and from a statistic view, we propose a effective coarse-to-fine algorithm to detect and register a small scale SFM point cloud in a large scale Lidar point cloud.

Globally Variance-Constrained Sparse Representation and Its Application in Image Set Coding

no code implementations17 Aug 2016 Xiang Zhang, Jiarui Sun, Siwei Ma, Zhouchen Lin, Jian Zhang, Shiqi Wang, Wen Gao

Therefore, introducing an accurate rate-constraint in sparse coding and dictionary learning becomes meaningful, which has not been fully exploited in the context of sparse representation.

Data Compression Dictionary Learning

SSDH: Semi-supervised Deep Hashing for Large Scale Image Retrieval

no code implementations28 Jul 2016 Jian Zhang, Yuxin Peng

(2) A semi-supervised deep hashing network is designed to extensively exploit both labeled and unlabeled data, in which we propose an online graph construction method to benefit from the evolving deep features during training to better capture semantic neighbors.

graph construction Image Retrieval +2

Parallel SGD: When does averaging help?

no code implementations23 Jun 2016 Jian Zhang, Christopher De Sa, Ioannis Mitliagkas, Christopher Ré

Consider a number of workers running SGD independently on the same pool of data and averaging the models every once in a while -- a common but not well understood practice.

SQuAD: 100,000+ Questions for Machine Comprehension of Text

18 code implementations EMNLP 2016 Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, Percy Liang

We present the Stanford Question Answering Dataset (SQuAD), a new reading comprehension dataset consisting of 100, 000+ questions posed by crowdworkers on a set of Wikipedia articles, where the answer to each question is a segment of text from the corresponding reading passage.

Question Answering Reading Comprehension

A Tool for Computing and Estimating the Volume of the Solution Space of SMT(LA)

no code implementations1 Jul 2015 Cunjing Ge, Feifei Ma, Jian Zhang

There are already quite a few tools for solving the Satisfiability Modulo Theories (SMT) problems.

Image Denoising via Adaptive Soft-Thresholding Based on Non-Local Samples

no code implementations CVPR 2015 Hangfan Liu, Ruiqin Xiong, Jian Zhang, Wen Gao

To estimate the expectation and variance parameters for the transform bands of a particular patch, we exploit the non-local correlation of image and collect a set of similar patches as data samples to form the distribution.

Image Denoising

Message Passing Inference for Large Scale Graphical Models with High Order Potentials

no code implementations NeurIPS 2014 Jian Zhang, Alex Schwing, Raquel Urtasun

To keep up with the Big Data challenge, parallelized algorithms based on dual decomposition have been proposed to perform inference in Markov random fields.

Semantic Segmentation

Abrupt Motion Tracking via Nearest Neighbor Field Driven Stochastic Sampling

no code implementations28 Oct 2014 Tianfei Zhou, Yao Lu, Feng Lv, Huijun Di, Qingjie Zhao, Jian Zhang

Stochastic sampling based trackers have shown good performance for abrupt motion tracking so that they have gained popularity in recent years.

Motion Detection

Group-based Sparse Representation for Image Restoration

1 code implementation14 May 2014 Jian Zhang, Debin Zhao, Wen Gao

In this paper, instead of using patch as the basic unit of sparse representation, we exploit the concept of group as the basic unit of sparse representation, which is composed of nonlocal patches with similar structures, and establish a novel sparse representation modeling of natural images, called group-based sparse representation (GSR).

Compressive Sensing Deblurring +4

Image Restoration Using Joint Statistical Modeling in Space-Transform Domain

no code implementations11 May 2014 Jian Zhang, Debin Zhao, Ruiqin Xiong, Siwei Ma, Wen Gao

This paper presents a novel strategy for high-fidelity image restoration by characterizing both local smoothness and nonlocal self-similarity of natural images in a unified statistical manner.

Deblurring Image Deblurring +3

Image Compressive Sensing Recovery Using Adaptively Learned Sparsifying Basis via L0 Minimization

no code implementations30 Apr 2014 Jian Zhang, Chen Zhao, Debin Zhao, Wen Gao

From many fewer acquired measurements than suggested by the Nyquist sampling theory, compressive sensing (CS) theory demonstrates that, a signal can be reconstructed with high probability when it exhibits sparsity in some domain.

Compressive Sensing

Spatially Directional Predictive Coding for Block-based Compressive Sensing of Natural Images

no code implementations29 Apr 2014 Jian Zhang, Debin Zhao, Feng Jiang

At the encoder, for each block of compressive sensing (CS) measurements, the optimal pre-diction is selected from a set of prediction candidates that are generated by four designed directional predictive modes.

Compressive Sensing

Structural Group Sparse Representation for Image Compressive Sensing Recovery

no code implementations29 Apr 2014 Jian Zhang, Debin Zhao, Feng Jiang, Wen Gao

Compressive Sensing (CS) theory shows that a signal can be decoded from many fewer measurements than suggested by the Nyquist sampling theory, when the signal is sparse in some domain.

Compressive Sensing

Characterizing A Database of Sequential Behaviors with Latent Dirichlet Hidden Markov Models

no code implementations24 May 2013 Yin Song, Longbing Cao, Xuhui Fan, Wei Cao, Jian Zhang

These sequence-level latent parameters for each sequence are modeled as latent Dirichlet random variables and parameterized by a set of deterministic database-level hyper-parameters.

General Classification

Face Detection with Effective Feature Extraction

no code implementations29 Sep 2010 Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhang

There is an abundant literature on face detection due to its important role in many vision applications.

Face Detection