Search Results for author: Lei Zhu

Found 144 papers, 73 papers with code

Dynamic Backtracking in GFlowNets: Enhancing Decision Steps with Reward-Dependent Adjustment Mechanisms

no code implementations8 Apr 2024 Shuai Guo, Jielei Chu, Lei Zhu, Tianrui Li

Generative Flow Networks (GFlowNets) are probabilistic models predicated on Markov flows, employing specific amortization algorithms to learn stochastic policies that generate compositional substances including biomolecules, chemical materials, and more.

Decision Making

Inverse Rendering of Glossy Objects via the Neural Plenoptic Function and Radiance Fields

no code implementations24 Mar 2024 Haoyuan Wang, WenBo Hu, Lei Zhu, Rynson W. H. Lau

Our method has two stages: the geometry of the target object and the pre-filtered environmental radiance fields are reconstructed in the first stage, and materials of the target object are estimated in the second stage with the proposed NeP and material-aware cone sampling strategy.

Inverse Rendering Object

Analytic-Splatting: Anti-Aliased 3D Gaussian Splatting via Analytic Integration

no code implementations17 Mar 2024 Zhihao Liang, Qi Zhang, WenBo Hu, Ying Feng, Lei Zhu, Kui Jia

This is because 3DGS treats each pixel as an isolated, single point rather than as an area, causing insensitivity to changes in the footprints of pixels.

Genuine Knowledge from Practice: Diffusion Test-Time Adaptation for Video Adverse Weather Removal

no code implementations12 Mar 2024 Yijun Yang, Hongtao Wu, Angelica I. Aviles-Rivero, Yulun Zhang, Jing Qin, Lei Zhu

Although ViWS-Net is proposed to remove adverse weather conditions in videos with a single set of pre-trained weights, it is seriously blinded by seen weather at train-time and degenerates when coming to unseen weather during test-time.

Test-time Adaptation

Beyond Text: Frozen Large Language Models in Visual Signal Comprehension

1 code implementation12 Mar 2024 Lei Zhu, Fangyun Wei, Yanye Lu

To achieve this, we present the Vision-to-Language Tokenizer, abbreviated as V2T Tokenizer, which transforms an image into a ``foreign language'' with the combined aid of an encoder-decoder, the LLM vocabulary, and a CLIP model.

Deblurring Image Captioning +5

Agile Multi-Source-Free Domain Adaptation

1 code implementation8 Mar 2024 Xinyao Li, Jingjing Li, Fengling Li, Lei Zhu, Ke Lu

Efficiently utilizing rich knowledge in pretrained models has become a critical topic in the era of large models.

Source-Free Domain Adaptation Specificity

Domain-Agnostic Mutual Prompting for Unsupervised Domain Adaptation

no code implementations5 Mar 2024 Zhekai Du, Xinyao Li, Fengling Li, Ke Lu, Lei Zhu, Jingjing Li

Specifically, the image contextual information is utilized to prompt the language branch in a domain-agnostic and instance-conditioned way.

Transfer Learning Unsupervised Domain Adaptation

Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning

no code implementations5 Mar 2024 Haoyu Chen, Wenbo Li, Jinjin Gu, Jingjing Ren, Haoze Sun, Xueyi Zou, Zhensong Zhang, Youliang Yan, Lei Zhu

Leveraging unseen LR images for self-supervised learning guides the model to adapt its modeling space to the target domain, facilitating fine-tuning of SR models without requiring paired high-resolution (HR) images.

Image Super-Resolution Self-Supervised Learning

Scribble Hides Class: Promoting Scribble-Based Weakly-Supervised Semantic Segmentation with Its Class Label

1 code implementation27 Feb 2024 Xinliang Zhang, Lei Zhu, Hangzhou He, Lujia Jin, Yanye Lu

In this study, we propose a class-driven scribble promotion network, which utilizes both scribble annotations and pseudo-labels informed by image-level classes and global semantics for supervision.

Segmentation Weakly supervised Semantic Segmentation +1

RelayAttention for Efficient Large Language Model Serving with Long System Prompts

1 code implementation22 Feb 2024 Lei Zhu, Xinjiang Wang, Wayne Zhang, Rynson W. H. Lau

Practical large language model (LLM) services may involve a long system prompt, which specifies the instructions, examples, and knowledge documents of the task and is reused across numerous requests.

Language Modelling Large Language Model

Data and Physics driven Deep Learning Models for Fast MRI Reconstruction: Fundamentals and Methodologies

no code implementations29 Jan 2024 Jiahao Huang, Yinzhe Wu, Fanwen Wang, Yingying Fang, Yang Nan, Cagan Alkan, Lei Xu, Zhifan Gao, Weiwen Wu, Lei Zhu, Zhaolin Chen, Peter Lally, Neal Bangerter, Kawin Setsompop, Yike Guo, Daniel Rueckert, Ge Wang, Guang Yang

Magnetic Resonance Imaging (MRI) is a pivotal clinical diagnostic tool, yet its extended scanning times often compromise patient comfort and image quality, especially in volumetric, temporal and quantitative scans.

Federated Learning MRI Reconstruction

Vivim: a Video Vision Mamba for Medical Video Object Segmentation

1 code implementation25 Jan 2024 Yijun Yang, Zhaohu Xing, Chunwang Huang, Lei Zhu

Traditional convolutional neural networks have a limited receptive field while transformer-based networks are mediocre in constructing long-term dependency from the perspective of computational complexity.

Lesion Segmentation Segmentation +3

SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation

1 code implementation24 Jan 2024 Zhaohu Xing, Tian Ye, Yijun Yang, Guang Liu, Lei Zhu

Our SegMamba, in contrast to Transformer-based methods, excels in whole volume feature modeling from a state space model standpoint, maintaining superior processing speed, even with volume features at a resolution of {$64\times 64\times 64$}.

Image Segmentation Medical Image Segmentation +1

SuperCLUE-Math6: Graded Multi-Step Math Reasoning Benchmark for LLMs in Chinese

no code implementations22 Jan 2024 Liang Xu, Hang Xue, Lei Zhu, Kangkang Zhao

We introduce SuperCLUE-Math6(SC-Math6), a new benchmark dataset to evaluate the mathematical reasoning abilities of Chinese language models.

GSM8K Math +1

EPA: Neural Collapse Inspired Robust Out-of-Distribution Detector

no code implementations3 Jan 2024 Jiawei Zhang, Yufan Chen, Cheng Jin, Lei Zhu, Yuantao Gu

Out-of-distribution (OOD) detection plays a crucial role in ensuring the security of neural networks.

Out of Distribution (OOD) Detection

Towards Flexible, Scalable, and Adaptive Multi-Modal Conditioned Face Synthesis

no code implementations26 Dec 2023 Jingjing Ren, Cheng Xu, Haoyu Chen, Xinran Qin, Lei Zhu

Recent progress in multi-modal conditioned face synthesis has enabled the creation of visually striking and accurately aligned facial images.

Denoising Face Generation

SC-Safety: A Multi-round Open-ended Question Adversarial Safety Benchmark for Large Language Models in Chinese

no code implementations9 Oct 2023 Liang Xu, Kangkang Zhao, Lei Zhu, Hang Xue

To systematically assess the safety of Chinese LLMs, we introduce SuperCLUE-Safety (SC-Safety) - a multi-round adversarial benchmark with 4912 open-ended questions covering more than 20 safety sub-dimensions.

Model Selection Natural Language Understanding

Shifting More Attention to Breast Lesion Segmentation in Ultrasound Videos

1 code implementation3 Oct 2023 Junhao Lin, Qian Dai, Lei Zhu, Huazhu Fu, Qiong Wang, Weibin Li, Wenhao Rao, Xiaoyang Huang, Liansheng Wang

We also devise a localization-based contrastive loss to reduce the lesion location distance between neighboring video frames within the same video and enlarge the location distances between frames from different ultrasound videos.

Lesion Segmentation Segmentation +1

Video Adverse-Weather-Component Suppression Network via Weather Messenger and Adversarial Backpropagation

1 code implementation ICCV 2023 Yijun Yang, Angelica I. Aviles-Rivero, Huazhu Fu, Ye Liu, Weiming Wang, Lei Zhu

In this work, we propose the first framework for restoring videos from all adverse weather conditions by developing a video adverse-weather-component suppression network (ViWS-Net).

Multi-level Asymmetric Contrastive Learning for Medical Image Segmentation Pre-training

no code implementations21 Sep 2023 Shuang Zeng, Lei Zhu, Xinliang Zhang, Zifeng Tian, Qian Chen, Lujia Jin, Jiayi Wang, Yanye Lu

In this work, we propose a novel asymmetric contrastive learning framework named JCL for medical image segmentation with self-supervised pre-training.

Contrastive Learning Image Segmentation +3

Towards Self-Adaptive Pseudo-Label Filtering for Semi-Supervised Learning

no code implementations18 Sep 2023 Lei Zhu, Zhanghan Ke, Rynson Lau

In this work, we observe that the distribution gap between the confidence values of correct and incorrect pseudo labels emerges at the very beginning of the training, which can be utilized to filter pseudo labels.

Pseudo Label Pseudo Label Filtering

Cross-Modal Retrieval: A Systematic Review of Methods and Future Directions

1 code implementation28 Aug 2023 Fengling Li, Lei Zhu, Tianshi Wang, Jingjing Li, Zheng Zhang, Heng Tao Shen

With the exponential surge in diverse multi-modal data, traditional uni-modal retrieval methods struggle to meet the needs of users demanding access to data from various modalities.

Cross-Modal Retrieval Retrieval

Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streaks

1 code implementation ICCV 2023 Sixiang Chen, Tian Ye, Jinbin Bai, ErKang Chen, Jun Shi, Lei Zhu

In the real world, image degradations caused by rain often exhibit a combination of rain streaks and raindrops, thereby increasing the challenges of recovering the underlying clean image.

Rain Removal

Federated Pseudo Modality Generation for Incomplete Multi-Modal MRI Reconstruction

no code implementations20 Aug 2023 Yunlu Yan, Chun-Mei Feng, Yuexiang Li, Rick Siow Mong Goh, Lei Zhu

In this paper, we propose a novel communication-efficient federated learning framework, namely Fed-PMG, to address the missing modality challenge in federated multi-modal MRI reconstruction.

Federated Learning MRI Reconstruction

Rethinking Client Drift in Federated Learning: A Logit Perspective

no code implementations20 Aug 2023 Yunlu Yan, Chun-Mei Feng, Mang Ye, WangMeng Zuo, Ping Li, Rick Siow Mong Goh, Lei Zhu, C. L. Philip Chen

Concretely, FedCSD introduces a class prototype similarity distillation to align the local logits with the refined global logits that are weighted by the similarity between local logits and the global prototype.

Federated Learning

Video-Instrument Synergistic Network for Referring Video Instrument Segmentation in Robotic Surgery

no code implementations18 Aug 2023 Hongqiu Wang, Lei Zhu, Guang Yang, Yike Guo, Shichen Zhang, Bo Xu, Yueming Jin

Our method is verified on these datasets, and experimental results exhibit that the VIS-Net can significantly outperform existing state-of-the-art referring segmentation methods.

Robot Navigation Segmentation

Branches Mutual Promotion for End-to-End Weakly Supervised Semantic Segmentation

no code implementations9 Aug 2023 Lei Zhu, Hangzhou He, Xinliang Zhang, Qian Chen, Shuang Zeng, Qiushi Ren, Yanye Lu

Existing methods adopt an online-trained classification branch to provide pseudo annotations for supervising the segmentation branch.

Classification Segmentation +3

SuperCLUE: A Comprehensive Chinese Large Language Model Benchmark

no code implementations27 Jul 2023 Liang Xu, Anqi Li, Lei Zhu, Hang Xue, Changtai Zhu, Kangkang Zhao, Haonan He, Xuanwei Zhang, Qiyue Kang, Zhenzhong Lan

We fill this gap by proposing a comprehensive Chinese benchmark SuperCLUE, named after another popular Chinese LLM benchmark CLUE.

Language Modelling Large Language Model

A Simple Data Augmentation for Feature Distribution Skewed Federated Learning

no code implementations14 Jun 2023 Yunlu Yan, Lei Zhu

To achieve this goal, we propose FedRDN, a simple yet remarkably effective data augmentation method for feature distribution skewed FL, which randomly injects the statistics of the dataset from the entire federation into the client's data.

Data Augmentation Federated Learning

Dynamic Interactive Relation Capturing via Scene Graph Learning for Robotic Surgical Report Generation

no code implementations5 Jun 2023 Hongqiu Wang, Yueming Jin, Lei Zhu

For robot-assisted surgery, an accurate surgical report reflects clinical operations during surgery and helps document entry tasks, post-operative analysis and follow-up treatment.

Graph Learning Relation

Cross-Modal Vertical Federated Learning for MRI Reconstruction

no code implementations5 Jun 2023 Yunlu Yan, Hong Wang, Yawen Huang, Nanjun He, Lei Zhu, Yuexiang Li, Yong Xu, Yefeng Zheng

To this end, we formulate this practical-yet-challenging cross-modal vertical federated learning task, in which shape data from multiple hospitals have different modalities with a small amount of multi-modality data collected from the same individuals.

Disentanglement MRI Reconstruction +1

Identity-Guided Collaborative Learning for Cloth-Changing Person Reidentification

no code implementations10 Apr 2023 Zan Gao, Shenxun Wei, Weili Guan, Lei Zhu, Meng Wang, Shenyong Chen

Moreover, human semantic information and pedestrian identity information are not fully explored.

Automated Prompting for Non-overlapping Cross-domain Sequential Recommendation

no code implementations9 Apr 2023 Lei Guo, Chunxiao Wang, Xinhua Wang, Lei Zhu, Hongzhi Yin

Cross-domain Recommendation (CR) has been extensively studied in recent years to alleviate the data sparsity issue in recommender systems by utilizing different domain information.

Sequential Recommendation

Multi-Behavior Recommendation with Cascading Graph Convolution Networks

1 code implementation28 Mar 2023 Zhiyong Cheng, Sai Han, Fan Liu, Lei Zhu, Zan Gao, Yuxin Peng

Most existing multi-behavior models fail to capture such dependencies in a behavior chain for embedding learning.

Masked Image Training for Generalizable Deep Image Denoising

1 code implementation CVPR 2023 Haoyu Chen, Jinjin Gu, Yihao Liu, Salma Abdel Magid, Chao Dong, Qiong Wang, Hanspeter Pfister, Lei Zhu

To address this issue, we present a novel approach to enhance the generalization performance of denoising networks, known as masked training.

Image Denoising

Neural Preset for Color Style Transfer

1 code implementation CVPR 2023 Zhanghan Ke, Yuhao Liu, Lei Zhu, Nanxuan Zhao, Rynson W. H. Lau

In this paper, we present a Neural Preset technique to address the limitations of existing color style transfer methods, including visual artifacts, vast memory requirement, and slow style switching speed.

4k Color Normalization +4

Distribution Aligned Diffusion and Prototype-guided network for Unsupervised Domain Adaptive Segmentation

1 code implementation22 Mar 2023 Haipeng Zhou, Lei Zhu, Yuyin Zhou

In order to explore its potential further, we have taken a step forward and considered a more complex scenario in the medical image domain, specifically, under an unsupervised adaptation condition.

DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification

1 code implementation19 Mar 2023 Yijun Yang, Huazhu Fu, Angelica I. Aviles-Rivero, Carola-Bibiane Schönlieb, Lei Zhu

However, while a substantial amount of diffusion-based research has focused on generative tasks, few studies have applied diffusion models to general medical image classification.

Diabetic Retinopathy Grading Image Classification +3

Diff-UNet: A Diffusion Embedded Network for Volumetric Segmentation

1 code implementation18 Mar 2023 Zhaohu Xing, Liang Wan, Huazhu Fu, Guang Yang, Lei Zhu

Our experimental results also indicate the universality and effectiveness of the proposed model.

Denoising Segmentation

HybridMIM: A Hybrid Masked Image Modeling Framework for 3D Medical Image Segmentation

1 code implementation18 Mar 2023 Zhaohu Xing, Lei Zhu, Lequan Yu, Zhiheng Xing, Liang Wan

Masked image modeling (MIM) with transformer backbones has recently been exploited as a powerful self-supervised pre-training technique.

Contrastive Learning Image Segmentation +3

Learning Physical-Spatio-Temporal Features for Video Shadow Removal

no code implementations16 Mar 2023 Zhihao Chen, Liang Wan, Yefan Xiao, Lei Zhu, Huazhu Fu

Then, we develop a progressive aggregation module to enhance the spatio and temporal characteristics of features maps, and effectively integrate the three kinds of features.

Shadow Removal Video Restoration

GeoSpark: Sparking up Point Cloud Segmentation with Geometry Clue

no code implementations14 Mar 2023 Zhening Huang, Xiaoyang Wu, Hengshuang Zhao, Lei Zhu, Shujun Wang, Georgios Hadjidemetriou, Ioannis Brilakis

For feature aggregation, it improves feature modeling by allowing the network to learn from both local points and neighboring geometry partitions, resulting in an enlarged data-tailored receptive field.

Point Cloud Segmentation

A Comprehensive Survey on Source-free Domain Adaptation

no code implementations23 Feb 2023 Zhiqi Yu, Jingjing Li, Zhekai Du, Lei Zhu, Heng Tao Shen

Over the past decade, domain adaptation has become a widely studied branch of transfer learning that aims to improve performance on target domains by leveraging knowledge from the source domain.

Source-Free Domain Adaptation Transfer Learning

One-Pot Multi-Frame Denoising

no code implementations18 Feb 2023 Lujia Jin, Shi Zhao, Lei Zhu, Qian Chen, Yanye Lu

Therefore, it is necessary to avoid the restriction of clean labels and make full use of noisy data for model training.


Learning to Control and Coordinate Mixed Traffic Through Robot Vehicles at Complex and Unsignalized Intersections

1 code implementation12 Jan 2023 Dawei Wang, Weizi Li, Lei Zhu, Jia Pan

In contrast, without RVs, congestion starts to develop when the traffic demand reaches as low as 200 vehicles per hour.

Multi-agent Reinforcement Learning

ReAssigner: A Plug-and-Play Virtual Machine Scheduling Intensifier for Heterogeneous Requests

no code implementations29 Nov 2022 Haochuan Cui, Junjie Sheng, Bo Jin, Yiqiu Hu, Li Su, Lei Zhu, Wenli Zhou, Xiangfeng Wang

With the rapid development of cloud computing, virtual machine scheduling has become one of the most important but challenging issues for the cloud computing community, especially for practical heterogeneous request sequences.

Cloud Computing Scheduling

Who is Gambling? Finding Cryptocurrency Gamblers Using Multi-modal Retrieval Methods

1 code implementation27 Nov 2022 Zhengjie Huang, Zhenguang Liu, Jianhai Chen, Qinming He, Shuang Wu, Lei Zhu, Meng Wang

Meanwhile, decentralized applications have also attracted intense attention from the online gambling community, with more and more decentralized gambling platforms created through the help of smart contracts.


CAMO-MOT: Combined Appearance-Motion Optimization for 3D Multi-Object Tracking with Camera-LiDAR Fusion

no code implementations6 Sep 2022 Li Wang, Xinyu Zhang, Wenyuan Qin, Xiaoyu Li, Lei Yang, Zhiwei Li, Lei Zhu, Hong Wang, Jun Li, Huaping Liu

As such, we propose a novel camera-LiDAR fusion 3D MOT framework based on the Combined Appearance-Motion Optimization (CAMO-MOT), which uses both camera and LiDAR data and significantly reduces tracking failures caused by occlusion and false detection.

3D Multi-Object Tracking Autonomous Driving +2

Joint Prediction of Meningioma Grade and Brain Invasion via Task-Aware Contrastive Learning

1 code implementation4 Sep 2022 Tianling Liu, Wennan Liu, Lequan Yu, Liang Wan, Tong Han, Lei Zhu

Preoperative and noninvasive prediction of the meningioma grade is important in clinical practice, as it directly influences the clinical decision making.

Contrastive Learning Decision Making +1

NestedFormer: Nested Modality-Aware Transformer for Brain Tumor Segmentation

1 code implementation31 Aug 2022 Zhaohu Xing, Lequan Yu, Liang Wan, Tong Han, Lei Zhu

Multi-modal MR imaging is routinely used in clinical practice to diagnose and investigate brain tumors by providing rich complementary information.

Brain Tumor Segmentation MRI segmentation +2

Bagging Regional Classification Activation Maps for Weakly Supervised Object Localization

1 code implementation16 Jul 2022 Lei Zhu, Qian Chen, Lujia Jin, Yunfei You, Yanye Lu

Classification activation map (CAM), utilizing the classification structure to generate pixel-wise localization maps, is a crucial mechanism for weakly supervised object localization (WSOL).

Object Weakly-Supervised Object Localization

Harmonizer: Learning to Perform White-Box Image and Video Harmonization

1 code implementation4 Jul 2022 Zhanghan Ke, Chunyi Sun, Lei Zhu, Ke Xu, Rynson W. H. Lau

Unlike prior methods that are based on black-box autoencoders, Harmonizer contains a neural network for filter argument prediction and several white-box filters (based on the predicted arguments) for image harmonization.

Image Harmonization Video Harmonization

A New Dataset and A Baseline Model for Breast Lesion Detection in Ultrasound Videos

2 code implementations1 Jul 2022 Zhi Lin, Junhao Lin, Lei Zhu, Huazhu Fu, Jing Qin, Liansheng Wang

Moreover, we learn video-level features to classify the breast lesions of the original video as benign or malignant lesions to further enhance the final breast lesion detection performance in ultrasound videos.

Lesion Classification Lesion Detection

Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential Recommendation

1 code implementation16 Jun 2022 Lei Guo, Jinyu Zhang, Li Tang, Tong Chen, Lei Zhu, Hongzhi Yin

Shared-account Cross-domain Sequential Recommendation (SCSR) task aims to recommend the next item via leveraging the mixed user behaviors in multiple domains.

Representation Learning Sequential Recommendation +1

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

3) To enhance texture details, we encode facial features with geometric guidance and employ local GANs to refine the face, feet, and hands.

Video Generation

RSCFed: Random Sampling Consensus Federated Semi-supervised Learning

1 code implementation CVPR 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.

Clinical Knowledge

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

1 code implementation CVPR 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 implementation CVPR 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 +2

Content-Noise Complementary Learning for Medical Image Denoising

2 code implementations IEEE Transactions on Medical Imaging 2022 Mufeng Geng, Xiangxi Meng, Jiangyuan Yu, Lei Zhu, Lujia Jin, Zhe Jiang, Bin Qiu, Hui Li, Hanjing Kong, Jianmin Yuan, Kun Yang, Hongming Shan, Hongbin Han, Zhi Yang, Qiushi Ren, Yanye Lu

In this study, we propose a simple yet effective strategy, the content-noise complementary learning (CNCL) strategy, in which two deep learning predictors are used to learn the respective content and noise of the image dataset complementarily.

Generative Adversarial Network Image Denoising +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.

Anatomy 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 object-detection +3

Distinguishing Unseen From Seen for Generalized Zero-Shot Learning

no code implementations CVPR 2022 Hongzu Su, Jingjing Li, Zhi Chen, Lei Zhu, Ke Lu

In this paper, we present a novel method which leverages both visual and semantic modalities to distinguish seen and unseen categories.

Generalized Zero-Shot Learning

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 Object +1

VMAgent: Scheduling Simulator for Reinforcement Learning

2 code implementations9 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.

Cloud Computing reinforcement-learning +2

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.

Image Segmentation Medical Image Segmentation +3

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.

Segmentation 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.

Inductive Bias Lesion Segmentation +2

HCDG: A Hierarchical Consistency Framework for Domain Generalization on Medical Image Segmentation

1 code implementation13 Sep 2021 Yijun Yang, Shujun Wang, Lei Zhu, Lequan Yu

Particularly, for the Extrinsic Consistency, we leverage the knowledge across multiple source domains to enforce data-level consistency.

Data Augmentation Domain Generalization +4

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

Bayesian Statistics Guided Label Refurbishment Mechanism: Mitigating Label Noise in Medical Image Classification

1 code implementation23 Jun 2021 Mengdi Gao, Ximeng Feng, Mufeng Geng, Zhe Jiang, Lei Zhu, Xiangxi Meng, Chuanqing Zhou, Qiushi Ren, Yanye Lu

BLRM utilizes maximum a posteriori probability (MAP) in the Bayesian statistics and the exponentially time-weighted technique to selectively correct the labels of noisy images.

Image Classification Medical Image Classification

Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation

1 code implementation CVPR 2021 Zhekai Du, Jingjing Li, Hongzu Su, Lei Zhu, Ke Lu

Previous bi-classifier adversarial learning methods only focus on the similarity between the outputs of two distinct classifiers.

Clustering Self-Supervised Learning +1

UGRec: Modeling Directed and Undirected Relations for Recommendation

1 code implementation10 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.

Attribute Collaborative Filtering +2

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 Image Segmentation +3

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 object-detection +1

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

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

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.

BIG-bench Machine Learning Management

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 +1

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.

Deep Hashing Image Retrieval +1

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 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.

Attribute 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.


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.


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 +3

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.

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

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

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

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.

Image Segmentation Medical Image Segmentation +2

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 Generative Adversarial Network +2

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.

feature selection

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 Retrieval

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.

Clustering Graph Clustering +1

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 Deep Hashing

Leveraging the Invariant Side of Generative Zero-Shot Learning

1 code implementation 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.

Object object-detection +2

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.

General Classification Multi Class Text 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.

Explainable Recommendation

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

2 code implementations12 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

2 code implementations 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

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.

object-detection RGB Salient Object Detection +2

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

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

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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