Search Results for author: Lei Zhu

Found 72 papers, 37 papers with code

Copy Motion From One to Another: Fake Motion Video Generation

no code implementations3 May 2022 Zhenguang Liu, Sifan Wu, Chejian Xu, Xiang Wang, Lei Zhu, Shuang Wu, Fuli Feng

Furthermore, current methods typically employ GANs with a L2 loss to assess the authenticity of the generated videos, inherently requiring a large amount of training samples to learn the texture details for adequate video generation.

Video Generation

RSCFed: Random Sampling Consensus Federated Semi-supervised Learning

1 code implementation26 Mar 2022 Xiaoxiao Liang, Yiqun Lin, Huazhu Fu, Lei Zhu, Xiaomeng Li

In this paper, we present a Random Sampling Consensus Federated learning, namely RSCFed, by considering the uneven reliability among models from fully-labeled clients, fully-unlabeled clients or partially labeled clients.

Federated Learning

Multi-modal learning for predicting the genotype of glioma

no code implementations21 Mar 2022 Yiran Wei, Xi Chen, Lei Zhu, Lipei Zhang, Carola-Bibiane Schönlieb, Stephen J. Price, Chao Li

In this study, we propose a multi-modal learning framework using three separate encoders to extract features of focal tumor image, tumor geometrics and global brain networks.

BoostMIS: Boosting Medical Image Semi-supervised Learning with Adaptive Pseudo Labeling and Informative Active Annotation

1 code implementation4 Mar 2022 Wenqiao Zhang, Lei Zhu, James Hallinan, Andrew Makmur, Shengyu Zhang, Qingpeng Cai, Beng Chin Ooi

In this paper, we propose a novel semi-supervised learning (SSL) framework named BoostMIS that combines adaptive pseudo labeling and informative active annotation to unleash the potential of medical image SSL models: (1) BoostMIS can adaptively leverage the cluster assumption and consistency regularization of the unlabeled data according to the current learning status.

Active Learning

Weakly Supervised Object Localization as Domain Adaption

1 code implementation3 Mar 2022 Lei Zhu, Qi She, Qian Chen, Yunfei You, Boyu Wang, Yanye Lu

To avoid this problem, this work provides a novel perspective that models WSOL as a domain adaption (DA) task, where the score estimator trained on the source/image domain is tested on the target/pixel domain to locate objects.

Classification Domain Adaptation +1

Motion Prediction via Joint Dependency Modeling in Phase Space

no code implementations7 Jan 2022 Pengxiang Su, Zhenguang Liu, Shuang Wu, Lei Zhu, Yifang Yin, Xuanjing Shen

In this paper, we introduce a novel convolutional neural model to effectively leverage explicit prior knowledge of motion anatomy, and simultaneously capture both spatial and temporal information of joint trajectory dynamics.

motion prediction

Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB Images

1 code implementation1 Jan 2022 Xiaoqiang Wang, Lei Zhu, Siliang Tang, Huazhu Fu, Ping Li, Fei Wu, Yi Yang, Yueting Zhuang

The depth estimation branch is trained with RGB-D images and then used to estimate the pseudo depth maps for all unlabeled RGB images to form the paired data.

Depth Estimation RGB-D Salient Object Detection +2

Background-aware Classification Activation Map for Weakly Supervised Object Localization

1 code implementation29 Dec 2021 Lei Zhu, Qi She, Qian Chen, Xiangxi Meng, Mufeng Geng, Lujia Jin, Zhe Jiang, Bin Qiu, Yunfei You, Yibao Zhang, Qiushi Ren, Yanye Lu

In our B-CAM, two image-level features, aggregated by pixel-level features of potential background and object locations, are used to purify the object feature from the object-related background and to represent the feature of the pure-background sample, respectively.

Classification Weakly-Supervised Object Localization

VMAgent: Scheduling Simulator for Reinforcement Learning

1 code implementation9 Dec 2021 Junjie Sheng, Shengliang Cai, Haochuan Cui, Wenhao Li, Yun Hua, Bo Jin, Wenli Zhou, Yiqiu Hu, Lei Zhu, Qian Peng, Hongyuan Zha, Xiangfeng Wang

A novel simulator called VMAgent is introduced to help RL researchers better explore new methods, especially for virtual machine scheduling.

reinforcement-learning

Network-wide Multi-step Traffic Volume Prediction using Graph Convolutional Gated Recurrent Neural Network

1 code implementation22 Nov 2021 Lei Lin, Weizi Li, Lei Zhu

For instance, our model reduces MAE by 25. 3%, RMSE by 29. 2%, and MAPE by 20. 2%, compared to the state-of-the-art Diffusion Convolutional Recurrent Neural Network (DCRNN) model using the hourly dataset.

Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Network

1 code implementation5 Nov 2021 Ge-Peng Ji, Lei Zhu, Mingchen Zhuge, Keren Fu

Camouflaged Object Detection (COD) aims to detect objects with similar patterns (e. g., texture, intensity, colour, etc) to their surroundings, and recently has attracted growing research interest.

Medical Image Segmentation Object Detection +1

Domain Adaptive Semantic Segmentation without Source Data

1 code implementation13 Oct 2021 Fuming You, Jingjing Li, Lei Zhu, Ke Lu, Zhi Chen, Zi Huang

To address these problems, we investigate domain adaptive semantic segmentation without source data, which assumes that the model is pre-trained on the source domain, and then adapting to the target domain without accessing source data anymore.

Semantic Segmentation

Boundary-aware Transformers for Skin Lesion Segmentation

1 code implementation8 Oct 2021 Jiacheng Wang, Lan Wei, Liansheng Wang, Qichao Zhou, Lei Zhu, Jing Qin

Skin lesion segmentation from dermoscopy images is of great importance for improving the quantitative analysis of skin cancer.

Lesion Segmentation Skin Lesion Segmentation

Towards Robust Cross-domain Image Understanding with Unsupervised Noise Removal

no code implementations9 Sep 2021 Lei Zhu, Zhaojing Luo, Wei Wang, Meihui Zhang, Gang Chen, Kaiping Zheng

In multimedia analysis, domain adaptation studies the problem of cross-domain knowledge transfer from a label rich source domain to a label scarce target domain, thus potentially alleviates the annotation requirement for deep learning models.

Domain Adaptation Transfer Learning

MT-ORL: Multi-Task Occlusion Relationship Learning

1 code implementation ICCV 2021 Panhe Feng, Qi She, Lei Zhu, Jiaxin Li, Lin Zhang, Zijian Feng, Changhu Wang, Chunpeng Li, Xuejing Kang, Anlong Ming

Retrieving occlusion relation among objects in a single image is challenging due to sparsity of boundaries in image.

From Synthetic to Real: Image Dehazing Collaborating with Unlabeled Real Data

1 code implementation6 Aug 2021 Ye Liu, Lei Zhu, Shunda Pei, Huazhu Fu, Jing Qin, Qing Zhang, Liang Wan, Wei Feng

Our DID-Net predicts the three component maps by progressively integrating features across scales, and refines each map by passing an independent refinement network.

Image Dehazing Single Image Dehazing

Unifying Nonlocal Blocks for Neural Networks

1 code implementation ICCV 2021 Lei Zhu, Qi She, Duo Li, Yanye Lu, Xuejing Kang, Jie Hu, Changhu Wang

The nonlocal-based blocks are designed for capturing long-range spatial-temporal dependencies in computer vision tasks.

Action Recognition Image Classification +2

Adversarial Energy Disaggregation for Non-intrusive Load Monitoring

no code implementations2 Aug 2021 Zhekai Du, Jingjing Li, Lei Zhu, Ke Lu, Heng Tao Shen

Energy disaggregation, also known as non-intrusive load monitoring (NILM), challenges the problem of separating the whole-home electricity usage into appliance-specific individual consumptions, which is a typical application of data analysis.

Non-Intrusive Load Monitoring

A Label Management Mechanism for Retinal Fundus Image Classification of Diabetic Retinopathy

no code implementations23 Jun 2021 Mengdi Gao, Ximeng Feng, Mufeng Geng, Zhe Jiang, Lei Zhu, Xiangxi Meng, Chuanqing Zhou, Qiushi Ren, Yanye Lu

Diabetic retinopathy (DR) remains the most prevalent cause of vision impairment and irreversible blindness in the working-age adults.

Image Classification

UGRec: Modeling Directed and Undirected Relations for Recommendation

no code implementations10 May 2021 Xinxiao Zhao, Zhiyong Cheng, Lei Zhu, Jiecai Zheng, Xueqing Li

In particular, for a directed relation, we transform the head and tail entities into the corresponding relation space to model their relation; and for an undirected co-occurrence relation, we project head and tail entities into a unique hyperplane in the entity space to minimize their distance.

Collaborative Filtering Recommendation Systems

DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation

no code implementations7 May 2021 Lei Guo, Li Tang, Tong Chen, Lei Zhu, Quoc Viet Hung Nguyen, Hongzhi Yin

Shared-account Cross-domain Sequential recommendation (SCSR) is the task of recommending the next item based on a sequence of recorded user behaviors, where multiple users share a single account, and their behaviours are available in multiple domains.

Sequential Recommendation Transfer Learning

Global Guidance Network for Breast Lesion Segmentation in Ultrasound Images

no code implementations5 Apr 2021 Cheng Xue, Lei Zhu, Huazhu Fu, Xiaowei Hu, Xiaomeng Li, Hai Zhang, Pheng Ann Heng

The BD modules learn additional breast lesion boundary map to enhance the boundary quality of a segmentation result refinement.

Boundary Detection Lesion Segmentation +1

Learning the Superpixel in a Non-iterative and Lifelong Manner

1 code implementation CVPR 2021 Lei Zhu, Qi She, Bin Zhang, Yanye Lu, Zhilin Lu, Duo Li, Jie Hu

Superpixel is generated by automatically clustering pixels in an image into hundreds of compact partitions, which is widely used to perceive the object contours for its excellent contour adherence.

Triple-cooperative Video Shadow Detection

1 code implementation CVPR 2021 Zhihao Chen, Liang Wan, Lei Zhu, Jia Shen, Huazhu Fu, Wennan Liu, Jing Qin

The bottleneck is the lack of a well-established dataset with high-quality annotations for video shadow detection.

Saliency Detection Semantic Segmentation +3

Feature-level Attentive ICF for Recommendation

1 code implementation22 Feb 2021 Zhiyong Cheng, Fan Liu, Shenghan Mei, Yangyang Guo, Lei Zhu, Liqiang Nie

To demonstrate the effectiveness of our method, we design a light attention neural network to integrate both item-level and feature-level attention for neural ICF models.

Collaborative Filtering Recommendation Systems

Interest-aware Message-Passing GCN for Recommendation

1 code implementation19 Feb 2021 Fan Liu, Zhiyong Cheng, Lei Zhu, Zan Gao, Liqiang Nie

To form the subgraphs, we design an unsupervised subgraph generation module, which can effectively identify users with common interests by exploiting both user feature and graph structure.

Deep Texture-Aware Features for Camouflaged Object Detection

no code implementations5 Feb 2021 Jingjing Ren, Xiaowei Hu, Lei Zhu, Xuemiao Xu, Yangyang Xu, Weiming Wang, Zijun Deng, Pheng-Ann Heng

Camouflaged object detection is a challenging task that aims to identify objects having similar texture to the surroundings.

Object Detection

A Unified Framework to Analyze and Design the Nonlocal Blocks for Neural Networks

no code implementations1 Jan 2021 Lei Zhu, Qi She, Changhu Wang

When choosing Chebyshev graph filter, a generalized formulation can be derived for explaining the existing nonlocal-based blocks (e. g. nonlocal block, nonlocal stage, double attention block) and uses to analyze their irrationality.

Action Recognition Fine-Grained Image Classification

Mitigating Intensity Bias in Shadow Detection via Feature Decomposition and Reweighting

no code implementations ICCV 2021 Lei Zhu, Ke Xu, Zhanghan Ke, Rynson W.H. Lau

These two phenomenons reveal that deep shadow detectors heavily depend on the intensity cue, which we refer to as intensity bias.

Shadow Detection

MLCask: Efficient Management of Component Evolution in Collaborative Data Analytics Pipelines

no code implementations17 Oct 2020 Zhaojing Luo, Sai Ho Yeung, Meihui Zhang, Kaiping Zheng, Lei Zhu, Gang Chen, Feiyi Fan, Qian Lin, Kee Yuan Ngiam, Beng Chin Ooi

In this paper, we identify two main challenges that arise during the deployment of machine learning pipelines, and address them with the design of versioning for an end-to-end analytics system MLCask.

Learning to Detect Specular Highlights from Real-world Images

1 code implementation10 Oct 2020 Gang Fu, Qing Zhang, QiFeng Lin, Lei Zhu, and Chunaxia Xiao

Specular highlight detection is a challenging problem, and has many applications such as shiny object detection and light source estimation.

Highlight Detection Object Detection

Dual-level Semantic Transfer Deep Hashing for Efficient Social Image Retrieval

1 code implementation10 Jun 2020 Lei Zhu, Hui Cui, Zhiyong Cheng, Jingjing Li, Zheng Zhang

Specifically, we design a complementary dual-level semantic transfer mechanism to efficiently discover the potential semantics of tags and seamlessly transfer them into binary hash codes.

Image Retrieval Representation Learning

Constrained Multi-shape Evolution for Overlapping Cytoplasm Segmentation

no code implementations8 Apr 2020 Youyi Song, Lei Zhu, Baiying Lei, Bin Sheng, Qi Dou, Jing Qin, Kup-Sze Choi

In the shape evolution, we compensate intensity deficiency for the segmentation by introducing not only the modeled local shape priors but also global shape priors (clump--level) modeled by considering mutual shape constraints of cytoplasms in the clump.

Task-adaptive Asymmetric Deep Cross-modal Hashing

no code implementations1 Apr 2020 Fengling Li, Tong Wang, Lei Zhu, Zheng Zhang, Xinhua Wang

Unlike previous cross-modal hashing approaches, our learning framework jointly optimizes semantic preserving that transforms deep features of multimedia data into binary hash codes, and the semantic regression which directly regresses query modality representation to explicit label.

Cross-Modal Retrieval

Multi-Feature Discrete Collaborative Filtering for Fast Cold-start Recommendation

no code implementations24 Mar 2020 Yang Xu, Lei Zhu, Zhiyong Cheng, Jingjing Li, Jiande Sun

Additionally, we develop a fast discrete optimization algorithm to directly compute the binary hash codes with simple operations.

Collaborative Filtering Quantization

A^2-GCN: An Attribute-aware Attentive GCN Model for Recommendation

no code implementations20 Mar 2020 Fan Liu, Zhiyong Cheng, Lei Zhu, Chenghao Liu, Liqiang Nie

Considering the fact that for different users, the attributes of an item have different influence on their preference for this item, we design a novel attention mechanism to filter the message passed from an item to a target user by considering the attribute information.

Recommendation Systems

Neural Networks Weights Quantization: Target None-retraining Ternary (TNT)

no code implementations18 Dec 2019 Tianyu Zhang, Lei Zhu, Qian Zhao, Kilho Shin

Quantization of weights of deep neural networks (DNN) has proven to be an effective solution for the purpose of implementing DNNs on edge devices such as mobiles, ASICs and FPGAs, because they have no sufficient resources to support computation involving millions of high precision weights and multiply-accumulate operations.

Quantization

DDNet: Dual-path Decoder Network for Occlusion Relationship Reasoning

no code implementations26 Nov 2019 Panhe Feng, Xuejing Kang, Lizhu Ye, Lei Zhu, Chunpeng Li, Anlong Ming

Besides, considering the restriction of occlusion orientation presentation to occlusion orientation learning, we design a new orthogonal representation for occlusion orientation and proposed the Orthogonal Orientation Regression loss which can get rid of the unfitness between occlusion representation and learning and further prompt the occlusion orientation learning.

CANet: Cross-disease Attention Network for Joint Diabetic Retinopathy and Diabetic Macular Edema Grading

1 code implementation4 Nov 2019 Xiaomeng Li, Xiao-Wei Hu, Lequan Yu, Lei Zhu, Chi-Wing Fu, Pheng-Ann Heng

In this paper, we present a novel cross-disease attention network (CANet) to jointly grade DR and DME by exploring the internal relationship between the diseases with only image-level supervision.

A Spectral Nonlocal Block for Neural Networks

no code implementations4 Nov 2019 Lei Zhu, Qi She, Lidan Zhang, Ping Guo

The nonlocal-based blocks are designed for capturing long-range spatial-temporal dependencies in computer vision tasks.

Action Recognition Fine-Grained Image Classification +2

Distribution Matching Prototypical Network for Unsupervised Domain Adaptation

no code implementations25 Sep 2019 Lei Zhu, Wei Wang, Mei Hui Zhang, Beng Chin Ooi, Chang Yao

State-of-the-art Unsupervised Domain Adaptation (UDA) methods learn transferable features by minimizing the feature distribution discrepancy between the source and target domains.

Unsupervised Domain Adaptation

Spectral Nonlocal Block for Neural Network

no code implementations25 Sep 2019 Lei Zhu, Qi She, Lidan Zhang, Ping Guo

The nonlocal network is designed for capturing long-range spatial-temporal dependencies in several computer vision tasks.

Video Classification

Alleviating Feature Confusion for Generative Zero-shot Learning

1 code implementation17 Sep 2019 Jingjing Li, Mengmeng Jing, Ke Lu, Lei Zhu, Yang Yang, Zi Huang

An inevitable issue of such a paradigm is that the synthesized unseen features are prone to seen references and incapable to reflect the novelty and diversity of real unseen instances.

Generalized Zero-Shot Learning

Cycle-consistent Conditional Adversarial Transfer Networks

1 code implementation17 Sep 2019 Jingjing Li, Erpeng Chen, Zhengming Ding, Lei Zhu, Ke Lu, Zi Huang

Domain adaptation investigates the problem of cross-domain knowledge transfer where the labeled source domain and unlabeled target domain have distinctive data distributions.

Domain Adaptation Transfer Learning

Personalized Hashtag Recommendation for Micro-videos

1 code implementation27 Aug 2019 Yinwei Wei, Zhiyong Cheng, Xuzheng Yu, Zhou Zhao, Lei Zhu, Liqiang Nie

The hashtags, that a user provides to a post (e. g., a micro-video), are the ones which in her mind can well describe the post content where she is interested in.

Enhancing Underexposed Photos using Perceptually Bidirectional Similarity

no code implementations25 Jul 2019 Qing Zhang, Yongwei Nie, Lei Zhu, Chunxia Xiao, Wei-Shi Zheng

To obtain high-quality results free of these artifacts, we present a novel underexposed photo enhancement approach that is able to maintain the perceptual consistency.

Video Enhancement

Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound

1 code implementation3 Jul 2019 Yi Wang, Haoran Dou, Xiao-Wei Hu, Lei Zhu, Xin Yang, Ming Xu, Jing Qin, Pheng-Ann Heng, Tianfu Wang, Dong Ni

Our attention module utilizes the attention mechanism to selectively leverage the multilevel features integrated from different layers to refine the features at each individual layer, suppressing the non-prostate noise at shallow layers of the CNN and increasing more prostate details into features at deep layers.

Medical Image Segmentation Semantic Segmentation

Probabilistic Multilayer Regularization Network for Unsupervised 3D Brain Image Registration

no code implementations3 Jul 2019 Lihao Liu, Xiaowei Hu, Lei Zhu, Pheng-Ann Heng

This paper presents a novel framework for unsupervised 3D brain image registration by capturing the feature-level transformation relationships between the unaligned image and reference image.

Image Registration

From Zero-Shot Learning to Cold-Start Recommendation

1 code implementation20 Jun 2019 Jingjing Li, Mengmeng Jing, Ke Lu, Lei Zhu, Yang Yang, Zi Huang

This work, for the first time, formulates CSR as a ZSL problem, and a tailor-made ZSL method is proposed to handle CSR.

Recommendation Systems Zero-Shot Learning

PAC-GAN: An Effective Pose Augmentation Scheme for Unsupervised Cross-View Person Re-identification

no code implementations5 Jun 2019 Chengyuan Zhang, Lei Zhu, Shichao Zhang

In this paper, we introduce a novel unsupervised pose augmentation cross-view person Re-Id scheme called PAC-GAN to overcome these limitations.

Cross-Modal Person Re-Identification Image Retrieval

Fusion-supervised Deep Cross-modal Hashing

no code implementations25 Apr 2019 Li Wang, Lei Zhu, En Yu, Jiande Sun, Huaxiang Zhang

Deep hashing has recently received attention in cross-modal retrieval for its impressive advantages.

Cross-Modal Retrieval

Exploring Auxiliary Context: Discrete Semantic Transfer Hashing for Scalable Image Retrieval

no code implementations25 Apr 2019 Lei Zhu, Zi Huang, Zhihui Li, Liang Xie, Heng Tao Shen

To address the problem, in this paper, we propose a novel hashing approach, dubbed as \emph{Discrete Semantic Transfer Hashing} (DSTH).

Content-Based Image Retrieval

Adaptive Collaborative Similarity Learning for Unsupervised Multi-view Feature Selection

no code implementations25 Apr 2019 Xiao Dong, Lei Zhu, Xuemeng Song, Jingjing Li, Zhiyong Cheng

We propose to dynamically learn the collaborative similarity structure, and further integrate it with the ultimate feature selection into a unified framework.

Discrete Optimal Graph Clustering

1 code implementation25 Apr 2019 Yudong Han, Lei Zhu, Zhiyong Cheng, Jingjing Li, Xiaobai Liu

2) the relaxing process of cluster labels may cause significant information loss.

Graph Clustering graph construction

Leveraging the Invariant Side of Generative Zero-Shot Learning

2 code implementations CVPR 2019 Jingjing Li, Mengmeng Jin, Ke Lu, Zhengming Ding, Lei Zhu, Zi Huang

In this paper, we take the advantage of generative adversarial networks (GANs) and propose a novel method, named leveraging invariant side GAN (LisGAN), which can directly generate the unseen features from random noises which are conditioned by the semantic descriptions.

Generalized Zero-Shot Learning

SAC-Net: Spatial Attenuation Context for Salient Object Detection

no code implementations25 Mar 2019 Xiaowei Hu, Chi-Wing Fu, Lei Zhu, Tianyu Wang, Pheng-Ann Heng

This paper presents a new deep neural network design for salient object detection by maximizing the integration of local and global image context within, around, and beyond the salient objects.

RGB Salient Object Detection Salient Object Detection

Explicit Interaction Model towards Text Classification

1 code implementation23 Nov 2018 Cunxiao Du, Zhaozheng Chin, Fuli Feng, Lei Zhu, Tian Gan, Liqiang Nie

To address this problem, we introduce the interaction mechanism to incorporate word-level matching signals into the text classification task.

Classification General Classification +3

MMALFM: Explainable Recommendation by Leveraging Reviews and Images

no code implementations12 Nov 2018 Zhiyong Cheng, Xiaojun Chang, Lei Zhu, Rose C. Kanjirathinkal, Mohan Kankanhalli

Then the aspect importance is integrated into a novel aspect-aware latent factor model (ALFM), which learns user's and item's latent factors based on ratings.

Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection

1 code implementation ECCV 2018 Lei Zhu, Zijun Deng, Xiao-Wei Hu, Chi-Wing Fu, Xuemiao Xu, Jing Qin, Pheng-Ann Heng

Second, we develop a bidirectional feature pyramid network (BFPN) to aggregate shadow contexts spanned across different CNN layers by deploying two series of RAR modules in the network to iteratively combine and refine context features: one series to refine context features from deep to shallow layers, and another series from shallow to deep layers.

Shadow Detection

Direction-aware Spatial Context Features for Shadow Detection and Removal

1 code implementation12 May 2018 Xiaowei Hu, Chi-Wing Fu, Lei Zhu, Jing Qin, Pheng-Ann Heng

This paper presents a novel deep neural network design for shadow detection and removal by analyzing the spatial image context in a direction-aware manner.

Shadow Detection And Removal Shadow Removal

Direction-aware Spatial Context Features for Shadow Detection

1 code implementation CVPR 2018 Xiaowei Hu, Lei Zhu, Chi-Wing Fu, Jing Qin, Pheng-Ann Heng

To achieve this, we first formulate the direction-aware attention mechanism in a spatial recurrent neural network (RNN) by introducing attention weights when aggregating spatial context features in the RNN.

Detecting Shadows Shadow Detection

Joint Bi-Layer Optimization for Single-Image Rain Streak Removal

no code implementations ICCV 2017 Lei Zhu, Chi-Wing Fu, Dani Lischinski, Pheng-Ann Heng

A third prior is defined on the rain-streak layer R, based on similarity of patches to the extracted rain patches.

Rain Removal

Leveraging Weak Semantic Relevance for Complex Video Event Classification

no code implementations ICCV 2017 Chao Li, Jiewei Cao, Zi Huang, Lei Zhu, Heng Tao Shen

In this paper, we propose a novel approach to automatically maximize the utility of weak semantic annotations (formalized as the semantic relevance of video shots to the target event) to facilitate video event classification.

Classification General Classification

Saliency Pattern Detection by Ranking Structured Trees

1 code implementation ICCV 2017 Lei Zhu, Haibin Ling, Jin Wu, Huiping Deng, Jin Liu

We show that the linear combination of structured labels can well model the saliency distribution in local regions.

RGB Salient Object Detection Saliency Prediction +1

Discrete Multi-modal Hashing with Canonical Views for Robust Mobile Landmark Search

no code implementations13 Jul 2017 Lei Zhu, Zi Huang, Xiaobai Liu, Xiangnan He, Jingkuan Song, Xiaofang Zhou

Finally, compact binary codes are learned on intermediate representation within a tailored discrete binary embedding model which preserves visual relations of images measured with canonical views and removes the involved noises.

A Non-Local Low-Rank Framework for Ultrasound Speckle Reduction

no code implementations CVPR 2017 Lei Zhu, Chi-Wing Fu, Michael S. Brown, Pheng-Ann Heng

`Speckle' refers to the granular patterns that occur in ultrasound images due to wave interference.

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