Search Results for author: Rui Li

Found 122 papers, 46 papers with code

Sparse Covariance Modeling in High Dimensions with Gaussian Processes

no code implementations NeurIPS 2018 Rui Li, Kishan Kc, Feng Cui, Justin Domke, Anne Haake

This paper studies statistical relationships among components of high-dimensional observations varying across non-random covariates.

Gaussian Processes Vocal Bursts Intensity Prediction

Treasures Outside Contexts: Improving Event Detection via Global Statistics

1 code implementation EMNLP 2021 Rui Li, Wenlin Zhao, Cheng Yang, Sen Su

Event detection (ED) aims at identifying event instances of specified types in given texts, which has been formalized as a sequence labeling task.

Event Detection

Reflection Separation via Multi-bounce Polarization State Tracing

no code implementations ECCV 2020 Rui Li, Simeng Qiu, Guangming Zang, Wolfgang Heidrich

Through a combination of a new polarization-guided image formation model and a novel supervised learning framework for the interpretation of a ray-tracing polarized image formation model, a general method is obtained to tackle general image reflection removal problems.

Reflection Removal

ShieldLM: Empowering LLMs as Aligned, Customizable and Explainable Safety Detectors

1 code implementation26 Feb 2024 Zhexin Zhang, Yida Lu, Jingyuan Ma, Di Zhang, Rui Li, Pei Ke, Hao Sun, Lei Sha, Zhifang Sui, Hongning Wang, Minlie Huang

The safety of Large Language Models (LLMs) has gained increasing attention in recent years, but there still lacks a comprehensive approach for detecting safety issues within LLMs' responses in an aligned, customizable and explainable manner.

Pan-Mamba: Effective pan-sharpening with State Space Model

no code implementations19 Feb 2024 Xuanhua He, Ke Cao, Keyu Yan, Rui Li, Chengjun Xie, Jie Zhang, Man Zhou

To the best of our knowledge, this work is the first attempt in exploring the potential of the Mamba model and establishes a new frontier in the pan-sharpening techniques.

Pansharpening

Similarity-based Neighbor Selection for Graph LLMs

1 code implementation6 Feb 2024 Rui Li, Jiwei Li, Jiawei Han, Guoyin Wang

Our research further underscores the significance of graph structure integration in LLM applications and identifies key factors for their success in node classification.

Node Classification

Boosting Multi-view Stereo with Late Cost Aggregation

1 code implementation22 Jan 2024 Jiang Wu, Rui Li, Yu Zhu, Wenxun Zhao, Jinqiu Sun, Yanning Zhang

To address this challenge, we present a late aggregation approach that allows for aggregating pairwise costs throughout the network feed-forward process, achieving accurate estimations with only minor changes of the plain CasMVSNet.

Blocking Geometric Matching

Minimally Supervised Learning using Topological Projections in Self-Organizing Maps

no code implementations12 Jan 2024 Zimeng Lyu, Alexander Ororbia, Rui Li, Travis Desell

In this work, we introduce a semi-supervised learning approach based on topological projections in self-organizing maps (SOMs), which significantly reduces the required number of labeled data points to perform parameter prediction, effectively exploiting information contained in large unlabeled datasets.

Decision Making Parameter Prediction +1

Frequency-Adaptive Pan-Sharpening with Mixture of Experts

no code implementations4 Jan 2024 Xuanhua He, Keyu Yan, Rui Li, Chengjun Xie, Jie Zhang, Man Zhou

Pan-sharpening involves reconstructing missing high-frequency information in multi-spectral images with low spatial resolution, using a higher-resolution panchromatic image as guidance.

Enhancing RAW-to-sRGB with Decoupled Style Structure in Fourier Domain

no code implementations4 Jan 2024 Xuanhua He, Tao Hu, Guoli Wang, Zejin Wang, Run Wang, Qian Zhang, Keyu Yan, Ziyi Chen, Rui Li, Chenjun Xie, Jie Zhang, Man Zhou

However, current methods often ignore the difference between cell phone RAW images and DSLR camera RGB images, a difference that goes beyond the color matrix and extends to spatial structure due to resolution variations.

Image Restoration

Power System Capacity Planning Considering Seasonal Hydrogen Storage by Salt Caverns

no code implementations21 Nov 2023 Xueqian He, Tianguang Lu, Jing Li, Wanxing Sheng, Rui Li

To minimize the overall operating cost, a comprehensive power system capacity planning model is proposed with the consideration of hydrogen storage in salt caverns, which is implemented by adopting an improved fast unit commitment method.

A Systematic Review for Transformer-based Long-term Series Forecasting

no code implementations31 Oct 2023 Liyilei Su, Xumin Zuo, Rui Li, Xin Wang, Heng Zhao, Bingding Huang

Various variants have enabled transformer architecture to effectively handle long-term time series forecasting (LTSF) tasks.

Time Series Time Series Forecasting

Are Human-generated Demonstrations Necessary for In-context Learning?

1 code implementation26 Sep 2023 Rui Li, Guoyin Wang, Jiwei Li

In this paper, we raise the fundamental question that whether human-generated demonstrations are necessary for ICL.

Arithmetic Reasoning Code Generation +4

Beyond Static Datasets: A Deep Interaction Approach to LLM Evaluation

no code implementations8 Sep 2023 Jiatong Li, Rui Li, Qi Liu

Existing LLM evaluation methods are mainly supervised signal-based which depends on static datasets and cannot evaluate the ability of LLMs in dynamic real-world scenarios where deep interaction widely exists.

Code Generation Machine Translation

Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models

1 code implementation7 Jun 2023 Rui Li, ST John, Arno Solin

Approximate inference in Gaussian process (GP) models with non-conjugate likelihoods gets entangled with the learning of the model hyperparameters.

Hyperparameter Optimization Variational Inference

Research on Multilingual News Clustering Based on Cross-Language Word Embeddings

no code implementations30 May 2023 Lin Wu, Rui Li, Wong-Hing Lam

(2) We use the LDA topic model to represent news as a combina-tion of cross-lingual vectors for headlines and topic probability distributions for con-tent, introducing concepts such as topic similarity to address the cross-lingual issue in news content representation.

Clustering Knowledge Distillation +3

The News Delivery Channel Recommendation Based on Granular Neural Network

no code implementations30 May 2023 Lin Wu, Rui Li, Jiaxuan Liu, Wong-Hing Lam

As is known, traditional news recommendation systems mostly employ techniques based on collaborative filtering and deep learning, but the performance of these algorithms is constrained by the sparsity of the data and the scalability of the approaches.

Collaborative Filtering Machine Translation +4

Black-box Source-free Domain Adaptation via Two-stage Knowledge Distillation

no code implementations13 May 2023 Shuai Wang, Daoan Zhang, Zipei Yan, Shitong Shao, Rui Li

In Stage \uppercase\expandafter{\romannumeral1}, we train the target model from scratch with soft pseudo-labels generated by the source model in a knowledge distillation manner.

Knowledge Distillation Source-Free Domain Adaptation +1

Towards Generalizable Medical Image Segmentation with Pixel-wise Uncertainty Estimation

no code implementations13 May 2023 Shuai Wang, Zipei Yan, Daoan Zhang, Zhongsen Li, Sirui Wu, Wenxuan Chen, Rui Li

In contrast, the IID hypothesis is not universally guaranteed in numerous real-world applications, especially in medical image analysis.

Image Segmentation Medical Image Segmentation +1

Learning to Fuse Monocular and Multi-view Cues for Multi-frame Depth Estimation in Dynamic Scenes

1 code implementation CVPR 2023 Rui Li, Dong Gong, Wei Yin, Hao Chen, Yu Zhu, Kaixuan Wang, Xiaozhi Chen, Jinqiu Sun, Yanning Zhang

To let the geometric perception learned from multi-view cues in static areas propagate to the monocular representation in dynamic areas and let monocular cues enhance the representation of multi-view cost volume, we propose a cross-cue fusion (CCF) module, which includes the cross-cue attention (CCA) to encode the spatially non-local relative intra-relations from each source to enhance the representation of the other.

Autonomous Driving Depth Estimation

Feature Alignment and Uniformity for Test Time Adaptation

1 code implementation CVPR 2023 Shuai Wang, Daoan Zhang, Zipei Yan, JianGuo Zhang, Rui Li

Test time adaptation (TTA) aims to adapt deep neural networks when receiving out of distribution test domain samples.

Domain Generalization Image Segmentation +3

LSwinSR: UAV Imagery Super-Resolution based on Linear Swin Transformer

1 code implementation17 Mar 2023 Rui Li, Xiaowei Zhao

Super-resolution, which aims to reconstruct high-resolution images from low-resolution images, has drawn considerable attention and has been intensively studied in computer vision and remote sensing communities.

Semantic Segmentation SSIM +1

Prototype Knowledge Distillation for Medical Segmentation with Missing Modality

1 code implementation17 Mar 2023 Shuai Wang, Zipei Yan, Daoan Zhang, Haining Wei, Zhongsen Li, Rui Li

Specifically, our ProtoKD can not only distillate the pixel-wise knowledge of multi-modality data to single-modality data but also transfer intra-class and inter-class feature variations, such that the student model could learn more robust feature representation from the teacher model and inference with only one single modality data.

Image Segmentation Knowledge Distillation +3

Bootstrap The Original Latent: Learning a Private Model from a Black-box Model

no code implementations7 Mar 2023 Shuai Wang, Daoan Zhang, JianGuo Zhang, Weiwei Zhang, Rui Li

In this paper, considering the balance of data/model privacy of model owners and user needs, we propose a new setting called Back-Propagated Black-Box Adaptation (BPBA) for users to better train their private models via the guidance of the back-propagated results of a Black-box foundation/source model.

Producing Usable Taxonomies Cheaply and Rapidly at Pinterest Using Discovered Dynamic $μ$-Topics

no code implementations29 Jan 2023 Abhijit Mahabal, Jiyun Luo, Rui Huang, Michael Ellsworth, Rui Li

Creating a taxonomy of interests is expensive and human-effort intensive: not only do we need to identify nodes and interconnect them, in order to use the taxonomy, we must also connect the nodes to relevant entities such as users, pins, and queries.

Specificity

Pyramid Dual Domain Injection Network for Pan-sharpening

1 code implementation ICCV 2023 Xuanhua He, Keyu Yan, Rui Li, Chengjun Xie, Jie Zhang, Man Zhou

To this end, we first revisit the degradation process of pan-sharpening in Fourier space, and then devise a Pyramid Dual Domain Injection Pan-sharpening Network upon the above observation by fully exploring and exploiting the distinguished information in both the spatial and frequency domains.

Spectral Super-Resolution Super-Resolution

Heterogeneous Diversity Driven Active Learning for Multi-Object Tracking

no code implementations ICCV 2023 Rui Li, Baopeng Zhang, Jun Liu, Wei Liu, Jian Zhao, Zhu Teng

HD-AMOT defines the diversified informative representation by encoding the geometric and semantic information, and formulates the frame inference strategy as a Markov decision process to learn an optimal sampling policy based on the designed informative representation.

Active Learning Multi-Object Tracking

A Large-scale Friend Suggestion Architecture

no code implementations24 Dec 2022 Lin Zhang, Rui Li

There has been little work on designing friend suggestion when facing these difficulties, and for the first time we aim to tackle this in large scale online games.

Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation

1 code implementation15 Dec 2022 Royson Lee, Rui Li, Stylianos I. Venieris, Timothy Hospedales, Ferenc Huszár, Nicholas D. Lane

Recent image degradation estimation methods have enabled single-image super-resolution (SR) approaches to better upsample real-world images.

Blind Super-Resolution Image Super-Resolution

Expanding Knowledge Graphs with Humans in the Loop

no code implementations10 Dec 2022 Emaad Manzoor, Jordan Tong, Sriniketh Vijayaraghavan, Rui Li

Concretely, given a knowledge graph, our method predicts the "parents" of new concepts to be added to this graph for further verification by human experts.

Knowledge Graphs

NRTR: Neuron Reconstruction with Transformer from 3D Optical Microscopy Images

no code implementations8 Dec 2022 Yijun Wang, Rui Lang, Rui Li, Junsong Zhang

Existing deep learning neuron reconstruction methods, although demonstrating exemplary performance, greatly demand complex rule-based components.

Predicting Biomedical Interactions with Probabilistic Model Selection for Graph Neural Networks

no code implementations22 Nov 2022 Kishan Kc, Rui Li, Paribesh Regmi, Anne R. Haake

Experiments on four interaction datasets show that our proposed method achieves accurate and calibrated predictions.

Model Selection

Towards Improved Learning in Gaussian Processes: The Best of Two Worlds

no code implementations11 Nov 2022 Rui Li, ST John, Arno Solin

Gaussian process training decomposes into inference of the (approximate) posterior and learning of the hyperparameters.

Binary Classification Gaussian Processes +3

Learning on Large-scale Text-attributed Graphs via Variational Inference

2 code implementations26 Oct 2022 Jianan Zhao, Meng Qu, Chaozhuo Li, Hao Yan, Qian Liu, Rui Li, Xing Xie, Jian Tang

In this paper, we propose an efficient and effective solution to learning on large text-attributed graphs by fusing graph structure and language learning with a variational Expectation-Maximization (EM) framework, called GLEM.

Variational Inference

The Future of Consumer Edge-AI Computing

no code implementations19 Oct 2022 Stefanos Laskaridis, Stylianos I. Venieris, Alexandros Kouris, Rui Li, Nicholas D. Lane

In the last decade, Deep Learning has rapidly infiltrated the consumer end, mainly thanks to hardware acceleration across devices.

Test-Time Training for Graph Neural Networks

no code implementations17 Oct 2022 Yiqi Wang, Chaozhuo Li, Wei Jin, Rui Li, Jianan Zhao, Jiliang Tang, Xing Xie

To bridge such gap, in this work we introduce the first test-time training framework for GNNs to enhance the model generalization capacity for the graph classification task.

Graph Classification Self-Supervised Learning +1

Accelerated partial separable model using dimension-reduced optimization technique for ultra-fast cardiac MRI

no code implementations2 Oct 2022 Zhongsen Li, Aiqi Sun, Chuyu Liu, Haining Wei, Shuai Wang, Mingzhu Fu, Rui Li

The main objective of this study is to accelerate the PS model, shorten the time required for acquisition and reconstruction, and maintain good image quality simultaneously.

Dimensionality Reduction Image Reconstruction

Spatial-then-Temporal Self-Supervised Learning for Video Correspondence

1 code implementation CVPR 2023 Rui Li, Dong Liu

Specifically, we firstly extract spatial features from unlabeled images via contrastive learning, and secondly enhance the features by exploiting the temporal cues in unlabeled videos via reconstructive learning.

Contrastive Learning Self-Supervised Learning

Learning Multi-Modal Brain Tumor Segmentation from Privileged Semi-Paired MRI Images with Curriculum Disentanglement Learning

no code implementations26 Aug 2022 Zecheng Liu, Jia Wei, Rui Li

Specifically, in the first step, we propose to conduct reconstruction and segmentation with augmented intra-modality style-consistent images.

Brain Tumor Segmentation Disentanglement +3

A Sahlqvist-style Correspondence Theorem for Linear-time Temporal Logic

no code implementations13 Jun 2022 Rui Li, Francesco Belardinelli

The main result of this paper is to prove the correspondence of LTL Sahlqvist formulas to frame conditions that are definable in first-order language.

A Look at Improving Robustness in Visual-inertial SLAM by Moment Matching

no code implementations27 May 2022 Arno Solin, Rui Li, Andrea Pilzer

The fusion of camera sensor and inertial data is a leading method for ego-motion tracking in autonomous and smart devices.

Unsupervised Multi-Modal Medical Image Registration via Discriminator-Free Image-to-Image Translation

1 code implementation28 Apr 2022 Zekang Chen, Jia Wei, Rui Li

In this paper, we propose a novel translation-based unsupervised deformable image registration approach to convert the multi-modal registration problem to a mono-modal one.

Computed Tomography (CT) Image Registration +3

HASA: Hybrid Architecture Search with Aggregation Strategy for Echinococcosis Classification and Ovary Segmentation in Ultrasound Images

no code implementations14 Apr 2022 Jikuan Qian, Rui Li, Xin Yang, Yuhao Huang, Mingyuan Luo, Zehui Lin, Wenhui Hong, Ruobing Huang, Haining Fan, Dong Ni, Jun Cheng

The hybrid framework consists of a pre-trained backbone and several searched cells (i. e., network building blocks), which takes advantage of the strengths of both NAS and the expert knowledge from existing convolutional neural networks.

Image Classification Neural Architecture Search +1

Semantic-guided Disentangled Representation for Unsupervised Cross-modality Medical Image Segmentation

no code implementations26 Mar 2022 Shuai Wang, Rui Li

Disentangled representation is a powerful technique to tackle domain shift problem in medical image analysis in unsupervised domain adaptation setting. However, previous methods only focus on exacting domain-invariant feature and ignore whether exacted feature is meaningful for downstream tasks. We propose a novel framework, called semantic-guided disentangled representation (SGDR), an effective method to exact semantically meaningful feature for segmentation task to improve performance of cross modality medical image segmentation in unsupervised domain adaptation setting.

Image Segmentation Medical Image Segmentation +3

Slice Imputation: Intermediate Slice Interpolation for Anisotropic 3D Medical Image Segmentation

no code implementations21 Mar 2022 Zhaotao Wu, Jia Wei, Jiabing Wang, Rui Li

We introduce a novel frame-interpolation-based method for slice imputation to improve segmentation accuracy for anisotropic 3D medical images, in which the number of slices and their corresponding segmentation labels can be increased between two consecutive slices in anisotropic 3D medical volumes.

Image Segmentation Imputation +3

Neural Adaptive SCEne Tracing

no code implementations28 Feb 2022 Rui Li, Darius Rückert, Yuanhao Wang, Ramzi Idoughi, Wolfgang Heidrich

Neural rendering with implicit neural networks has recently emerged as an attractive proposition for scene reconstruction, achieving excellent quality albeit at high computational cost.

Neural Rendering

HousE: Knowledge Graph Embedding with Householder Parameterization

1 code implementation16 Feb 2022 Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang

The effectiveness of knowledge graph embedding (KGE) largely depends on the ability to model intrinsic relation patterns and mapping properties.

Knowledge Graph Embedding Relation +1

NeAT: Neural Adaptive Tomography

1 code implementation4 Feb 2022 Darius Rückert, Yuanhao Wang, Rui Li, Ramzi Idoughi, Wolfgang Heidrich

Through a combination of neural features with an adaptive explicit representation, we achieve reconstruction times far superior to existing neural inverse rendering methods.

3D Reconstruction Inverse Rendering +2

Dilated Continuous Random Field for Semantic Segmentation

1 code implementation1 Feb 2022 Xi Mo, Xiangyu Chen, Cuncong Zhong, Rui Li, Kaidong Li, Usman Sajid

Mean field approximation methodology has laid the foundation of modern Continuous Random Field (CRF) based solutions for the refinement of semantic segmentation.

Semantic Segmentation

Motion-Focused Contrastive Learning of Video Representations

1 code implementation ICCV 2021 Rui Li, Yiheng Zhang, Zhaofan Qiu, Ting Yao, Dong Liu, Tao Mei

To this end, we compose a duet of exploiting the motion for data augmentation and feature learning in the regime of contrastive learning.

Contrastive Learning Data Augmentation +2

A New Perspective on the Effects of Spectrum in Graph Neural Networks

1 code implementation14 Dec 2021 Mingqi Yang, Yanming Shen, Rui Li, Heng Qi, Qiang Zhang, BaoCai Yin

Many improvements on GNNs can be deemed as operations on the spectrum of the underlying graph matrix, which motivates us to directly study the characteristics of the spectrum and their effects on GNN performance.

Graph Classification Graph Property Prediction +1

Building extraction with vision transformer

no code implementations29 Nov 2021 Libo Wang, Shenghui Fang, Rui Li, Xiaoliang Meng

Second, spatial details are not sufficiently preserved during the feature extraction of the Vision Transformer, resulting in the inability for fine-grained building segmentation.

Image Classification Object Detection +1

Joint Inference for Neural Network Depth and Dropout Regularization

2 code implementations NeurIPS 2021 Kishan K C, Rui Li, MohammadMahdi Gilany

We propose a unified Bayesian model selection method to jointly infer the most plausible network depth warranted by data, and perform dropout regularization simultaneously.

Continual Learning Model Selection

Shape and Reflectance Reconstruction in Uncontrolled Environments by Differentiable Rendering

no code implementations25 Oct 2021 Rui Li, Guangmin Zang, Miao Qi, Wolfgang Heidrich

Simultaneous reconstruction of geometry and reflectance properties in uncontrolled environments remains a challenging problem.

Novel View Synthesis

A Channel Coding Benchmark for Meta-Learning

1 code implementation15 Jul 2021 Rui Li, Ondrej Bohdal, Rajesh Mishra, Hyeji Kim, Da Li, Nicholas Lane, Timothy Hospedales

We use our MetaCC benchmark to study several aspects of meta-learning, including the impact of task distribution breadth and shift, which can be controlled in the coding problem.

Meta-Learning

Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images

1 code implementation23 Jun 2021 Libo Wang, Rui Li, Dongzhi Wang, Chenxi Duan, Teng Wang, Xiaoliang Meng

Specifically, the dependency path is conducted based on the ResT, a novel Transformer backbone with memory-efficient multi-head self-attention, while the texture path is built on the stacked convolution operation.

Autonomous Driving Decision Making +3

TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation

1 code implementation19 May 2021 Junxiao Chen, Jia Wei, Rui Li

In this paper, we propose a novel target-aware generative adversarial network called TarGAN, which is a generic multi-modality medical image translation model capable of (1) learning multi-modality medical image translation without relying on paired data, (2) enhancing quality of target area generation with the help of target area labels.

Generative Adversarial Network Translation

A unified Neural Network Approach to E-CommerceRelevance Learning

no code implementations26 Apr 2021 Yunjiang Jiang, Yue Shang, Rui Li, Wen-Yun Yang, Guoyu Tang, Chaoyi Ma, Yun Xiao, Eric Zhao

We describe a highly-scalable feed-forward neural model to provide relevance score for (query, item) pairs, using only user query and item title as features, and both user click feedback as well as limited human ratings as labels.

Information Retrieval Retrieval

A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images

1 code implementation25 Apr 2021 Libo Wang, Rui Li, Chenxi Duan, Ce Zhang, Xiaoliang Meng, Shenghui Fang

The fully convolutional network (FCN) with an encoder-decoder architecture has been the standard paradigm for semantic segmentation.

Ranked #3 on Semantic Segmentation on ISPRS Potsdam (using extra training data)

Segmentation Semantic Segmentation

From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search

no code implementations24 Mar 2021 Rui Li, Yunjiang Jiang, WenYun Yang, Guoyu Tang, Songlin Wang, Chaoyi Ma, wei he, Xi Xiong, Yun Xiao, Eric Yihong Zhao

We introduce deep learning models to the two most important stages in product search at JD. com, one of the largest e-commerce platforms in the world.

Re-Ranking Retrieval +1

Scale-aware Neural Network for Semantic Segmentation of Multi-resolution Remote Sensing Images

no code implementations14 Mar 2021 Libo Wang, Ce Zhang, Rui Li, Chenxi Duan, Xiaoliang Meng, Peter M. Atkinson

However, MSR images suffer from two critical issues: 1) increased scale variation of geo-objects and 2) loss of detailed information at coarse spatial resolutions.

Scene Understanding Segmentation +1

A2-FPN for Semantic Segmentation of Fine-Resolution Remotely Sensed Images

2 code implementations16 Feb 2021 Rui Li, Shunyi Zheng, Ce Zhang, Chenxi Duan, Libo Wang

Based on FPN and AAM, a novel framework named Attention Aggregation Feature Pyramid Network (A2-FPN) is developed for semantic segmentation of fine-resolution remotely sensed images.

Decision Making Scene Understanding +2

Learning Depth via Leveraging Semantics: Self-supervised Monocular Depth Estimation with Both Implicit and Explicit Semantic Guidance

no code implementations11 Feb 2021 Rui Li, Xiantuo He, Danna Xue, Shaolin Su, Qing Mao, Yu Zhu, Jinqiu Sun, Yanning Zhang

While the mappings between image and pixel-wise depth are well-studied in current methods, the correlation between image, depth and scene semantics, however, is less considered.

Monocular Depth Estimation

Adaptive Processor Frequency Adjustment for Mobile Edge Computing with Intermittent Energy Supply

no code implementations10 Feb 2021 Tiansheng Huang, Weiwei Lin, Xiaobin Hong, Xiumin Wang, Qingbo Wu, Rui Li, Ching-Hsien Hsu, Albert Y. Zomaya

With astonishing speed, bandwidth, and scale, Mobile Edge Computing (MEC) has played an increasingly important role in the next generation of connectivity and service delivery.

Edge-computing

ABCNet: Attentive Bilateral Contextual Network for Efficient Semantic Segmentation of Fine-Resolution Remote Sensing Images

1 code implementation4 Feb 2021 Rui Li, Chenxi Duan

Specifically, the high-caliber performance of the convolutional neural network (CNN) heavily relies on fine-grained spatial details (fine resolution) and sufficient contextual information (large receptive fields), both of which trigger high computational costs.

Segmentation Semantic Segmentation

Analytical Characterization and Design Space Exploration for Optimization of CNNs

1 code implementation24 Jan 2021 Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan

Moving data through the memory hierarchy is a fundamental bottleneck that can limit the performance of core algorithms of machine learning, such as convolutional neural networks (CNNs).

BIG-bench Machine Learning

Non-uniform Motion Deblurring with Blurry Component Divided Guidance

no code implementations15 Jan 2021 Pei Wang, Wei Sun, Qingsen Yan, Axi Niu, Rui Li, Yu Zhu, Jinqiu Sun, Yanning Zhang

To tackle the above problems, we present a deep two-branch network to deal with blurry images via a component divided module, which divides an image into two components based on the representation of blurry degree.

Blind Image Deblurring Image Deblurring +1

IntraTomo: Self-Supervised Learning-Based Tomography via Sinogram Synthesis and Prediction

1 code implementation ICCV 2021 Guangming Zang, Ramzi Idoughi, Rui Li, Peter Wonka, Wolfgang Heidrich

After getting estimated through the sinogram prediction module, the density field is consistently refined in the second module using local and non-local geometrical priors.

Computed Tomography (CT) Low-Dose X-Ray Ct Reconstruction +3

VIS30K: A Collection of Figures and Tables from IEEE Visualization Conference Publications

no code implementations22 Dec 2020 Jian Chen, Meng Ling, Rui Li, Petra Isenberg, Tobias Isenberg, Michael Sedlmair, Torsten Möller, Robert S. Laramee, Han-Wei Shen, Katharina Wünsche, Qiru Wang

We present the VIS30K dataset, a collection of 29, 689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST).

Multi-Head Linear Attention Generative Adversarial Network for Thin Cloud Removal

no code implementations20 Dec 2020 Chenxi Duan, Rui Li

In remote sensing images, the existence of the thin cloud is an inevitable and ubiquitous phenomenon that crucially reduces the quality of imageries and limits the scenarios of application.

Cloud Removal Generative Adversarial Network

Semantic-Guided Representation Enhancement for Self-supervised Monocular Trained Depth Estimation

no code implementations15 Dec 2020 Rui Li, Qing Mao, Pei Wang, Xiantuo He, Yu Zhu, Jinqiu Sun, Yanning Zhang

Based on this framework, we enhance the local feature representation by sampling and feeding the point-based features that locate on the semantic edges to an individual Semantic-guided Edge Enhancement module (SEEM), which is specifically designed for promoting depth estimation on the challenging semantic borders.

Depth Estimation Semantic Segmentation

Dynamic Fusion of Eye Movement Data and Verbal Narrations in Knowledge-rich Domains

no code implementations NeurIPS 2020 Ervine Zheng, Qi Yu, Rui Li, Pengcheng Shi, Anne Haake

We propose to jointly analyze experts' eye movements and verbal narrations to discover important and interpretable knowledge patterns to better understand their decision-making processes.

Decision Making

Multi-stage Attention ResU-Net for Semantic Segmentation of Fine-Resolution Remote Sensing Images

1 code implementation29 Nov 2020 Rui Li, Shunyi Zheng, Chenxi Duan, Jianlin Su, Ce Zhang

The attention mechanism can refine the extracted feature maps and boost the classification performance of the deep network, which has become an essential technique in computer vision and natural language processing.

Computational Efficiency Semantic Segmentation

Eliminating the Barriers: Demystifying Wi-Fi Baseband Design and Introducing the PicoScenes Wi-Fi Sensing Platform

2 code implementations20 Oct 2020 Zhiping Jiang, Tom H. Luan, Han Hao, Jing Wang, Xincheng Ren, Kun Zhao, Wei Xi, Yueshen Xu, Rui Li

Three barriers always hamper the research: unknown baseband design and its influence, inadequate hardware, and the lack of versatile and flexible measurement software.

Hardware Architecture

Interpretable Structured Learning with Sparse Gated Sequence Encoder for Protein-Protein Interaction Prediction

1 code implementation16 Oct 2020 Kishan Kc, Feng Cui, Anne Haake, Rui Li

Although various deep learning models in Siamese architecture have been proposed to model PPIs from sequences, these methods are computationally expensive for a large number of PPIs due to the pairwise encoding process.

Predicting Biomedical Interactions with Higher-Order Graph Convolutional Networks

1 code implementation16 Oct 2020 Kishan Kc, Rui Li, Feng Cui, Anne Haake

Recently, graph neural networks have been proposed to effectively learn representations for biomedical entities and achieved state-of-the-art results in biomedical interaction prediction.

Link Prediction

Multi-Attention-Network for Semantic Segmentation of Fine Resolution Remote Sensing Images

no code implementations3 Sep 2020 Rui Li, Shunyi Zheng, Chenxi Duan, Ce Zhang, Jianlin Su, P. M. Atkinson

A novel attention mechanism of kernel attention with linear complexity is proposed to alleviate the large computational demand in attention.

Management Segmentation +1

Thick Cloud Removal of Remote Sensing Images Using Temporal Smoothness and Sparsity-Regularized Tensor Optimization

no code implementations11 Aug 2020 Chenxi Duan, Jun Pan, Rui Li

In this paper, a novel thick cloud removal method for remote sensing images based on temporal smoothness and sparsity-regularized tensor optimization (TSSTO) is proposed.

Cloud Removal

Land Cover Classification from Remote Sensing Images Based on Multi-Scale Fully Convolutional Network

1 code implementation1 Aug 2020 Rui Li, Shunyi Zheng, Chenxi Duan, Ce Zhang

In this paper, a Multi-Scale Fully Convolutional Network (MSFCN) with multi-scale convolutional kernel is proposed to exploit discriminative representations from two-dimensional (2D) satellite images.

General Classification Land Cover Classification

Research on Fitness Function of Two Evolution Algorithms Used for Neutron Spectrum Unfolding

no code implementations30 Jul 2020 Rui Li, Jianbo Yang, Xianguo Tuo, Rui Shi

In this work, we investigated the performance of eight fitness functions attached to the genetic algorithm (GA) and the differential evolution algorithm (DEA) used for unfolding four neutron spectra selected from the IAEA 403 report.

Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation

2 code implementations29 Jul 2020 Rui Li, Jianlin Su, Chenxi Duan, Shunyi Zheng

In this paper, to remedy this deficiency, we propose a Linear Attention Mechanism which is approximate to dot-product attention with much less memory and computational costs.

Semantic Segmentation

MACU-Net for Semantic Segmentation of Fine-Resolution Remotely Sensed Images

2 code implementations26 Jul 2020 Rui Li, Chenxi Duan, Shunyi Zheng, Ce Zhang, Peter M. Atkinson

In this Letter, we incorporate multi-scale features generated by different layers of U-Net and design a multi-scale skip connected and asymmetric-convolution-based U-Net (MACU-Net), for segmentation using fine-resolution remotely sensed images.

Image Segmentation Management +3

Model Adaptation: Unsupervised Domain Adaptation Without Source Data

no code implementations CVPR 2020 Rui Li, Qianfen Jiao, Wenming Cao, Hau-San Wong, Si Wu

We aim to explore how to rely only on unlabeled target data to improve performance of an existing source prediction model on the target domain, since labeled source data may not be available in some real-world scenarios due to data privacy issues.

Clustering Unsupervised Domain Adaptation

LiteDenseNet: A Lightweight Network for Hyperspectral Image Classification

no code implementations17 Apr 2020 Rui Li, Chenxi Duan

Hyperspectral Image (HSI) classification based on deep learning has been an attractive area in recent years.

Classification General Classification +1

Robust Data Preprocessing for Machine-Learning-Based Disk Failure Prediction in Cloud Production Environments

no code implementations20 Dec 2019 Shujie Han, Jun Wu, Erci Xu, Cheng He, Patrick P. C. Lee, Yi Qiang, Qixing Zheng, Tao Huang, Zixi Huang, Rui Li

To provide proactive fault tolerance for modern cloud data centers, extensive studies have proposed machine learning (ML) approaches to predict imminent disk failures for early remedy and evaluated their approaches directly on public datasets (e. g., Backblaze SMART logs).

BIG-bench Machine Learning

Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes

no code implementations NeurIPS 2019 Rui Li

This paper studies statistical characteristics of multivariate observations with irregular changes in their covariance structures across input space.

Gaussian Processes

Validation of image-guided cochlear implant programming techniques

no code implementations23 Sep 2019 Yiyuan Zhao, Jianing Wang, Rui Li, Robert F. Labadie, Benoit M. Dawant, Jack H. Noble

In this article, we create a ground truth dataset with conventional CT and micro-CT images of 35 temporal bone specimens to both rigorously characterize the accuracy of these two steps and assess how inaccuracies in these steps affect the overall results.

Anatomy Segmentation

A Convolutional Neural Network with Mapping Layers for Hyperspectral Image Classification

no code implementations26 Aug 2019 Rui Li, Zhibin Pan, Yang Wang, Ping Wang

In this paper, we propose a convolutional neural network with mapping layers (MCNN) for hyperspectral image (HSI) classification.

Classification General Classification +1

Adaptive Noise Injection: A Structure-Expanding Regularization for RNN

no code implementations25 Jul 2019 Rui Li, Kai Shuang, Mengyu Gu, Sen Su

Due to the adaptive noises can be improved as the training processes, its negative effects can be weakened and even transformed into a positive effect to further improve the expressiveness of the main-branch RNN.

Language Modelling

Neural Embedding for Physical Manipulations

no code implementations13 Jul 2019 Lingzhi Zhang, Andong Cao, Rui Li, Jianbo Shi

In common real-world robotic operations, action and state spaces can be vast and sometimes unknown, and observations are often relatively sparse.

Use of OWL and Semantic Web Technologies at Pinterest

no code implementations3 Jul 2019 Rafael S. Gonçalves, Matthew Horridge, Rui Li, Yu Liu, Mark A. Musen, Csongor I. Nyulas, Evelyn Obamos, Dhananjay Shrouty, David Temple

In this paper, we present the engineering of an OWL ontology---the Pinterest Taxonomy---that forms the core of Pinterest's knowledge graph, the Pinterest Taste Graph.

Imitating Targets from all sides: An Unsupervised Transfer Learning method for Person Re-identification

no code implementations10 Apr 2019 Jiajie Tian, Zhu Teng, Rui Li, Yan Li, Baopeng Zhang, Jianping Fan

Person re-identification (Re-ID) models usually show a limited performance when they are trained on one dataset and tested on another dataset due to the inter-dataset bias (e. g. completely different identities and backgrounds) and the intra-dataset difference (e. g. camera invariance).

Person Re-Identification Transfer Learning

GNE: a deep learning framework for gene network inference by aggregating biological information

1 code implementation BMC Systems Biology 2019 Kishan KC, Rui Li, Feng Cui, Qi Yu, Anne R. Haake

However, it is still a challenging task to aggregate heterogeneous biological information such as gene expression and gene interactions to achieve more accurate inference for prediction and discovery of new gene interactions.

 Ranked #1 on Gene Interaction Prediction on BioGRID(yeast) (using extra training data)

Gene Interaction Prediction Link Prediction

Deep Distribution Regression

1 code implementation14 Mar 2019 Rui Li, Howard D. Bondell, Brian J. Reich

Due to their flexibility and predictive performance, machine-learning based regression methods have become an important tool for predictive modeling and forecasting.

Decision Making General Classification +2

Towards Machine Learning Prediction of Deep Brain Stimulation (DBS) Intra-operative Efficacy Maps

no code implementations26 Nov 2018 Camilo Bermudez, William Rodriguez, Yuankai Huo, Allison E. Hainline, Rui Li, Robert Shults, Pierre D. DHaese, Peter E. Konrad, Benoit M. Dawant, Bennett A. Landman

We show an improvement in the classification of intraoperative stimulation coordinates as a positive response in reduction of symptoms with AUC of 0. 670 compared to a baseline registration-based approach, which achieves an AUC of 0. 627 (p < 0. 01).

Anatomy BIG-bench Machine Learning +1

Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets with Multi-stream Inputs

no code implementations22 Nov 2018 Chaoyun Zhang, Rui Li, Woojin Kim, Daesub Yoon, Paul Patras

Experiments conducted with a dataset that we collect in a mock-up car environment demonstrate that the proposed InterCNN with MobileNet convolutional blocks can classify 9 different behaviors with 73. 97% accuracy, and 5 'aggregated' behaviors with 81. 66% accuracy.

Classification General Classification

Fast Symbolic 3D Registration Solution

4 code implementations12 May 2018 Jin Wu, Ming Liu, Zebo Zhou, Rui Li

3D registration has always been performed invoking singular value decomposition (SVD) or eigenvalue decomposition (EIG) in real engineering practices.

Participation of an energy hub in electricity and heat distribution markets: An mpec approach

1 code implementation IEEE Transactions on Smart Grid 2018 Rui Li, Wei Wei, Shengwei Mei, Qinran Hu, Qiuwei Wu

A mathematic program with equilibrium constraints (MPEC) model is proposed to study the strategic behaviors of a profit-driven energy hub in the electricity market and heating market under the background of energy system integration.

Patch-based Texture Synthesis for Image Inpainting

no code implementations5 May 2016 Tao Zhou, Brian Johnson, Rui Li

We form it as an optimization problem that identifies the potential patches for synthesis from an coarse-to-fine manner.

Image Inpainting Image Retrieval +2

Multiobjective Optimization of Classifiers by Means of 3-D Convex Hull Based Evolutionary Algorithm

no code implementations18 Dec 2014 Jiaqi Zhao, Vitor Basto Fernandes, Licheng Jiao, Iryna Yevseyeva, Asep Maulana, Rui Li, Thomas Bäck, Michael T. M. Emmerich

The design of the algorithm proposed in this paper is inspired by indicator-based evolutionary algorithms, where first a performance indicator for a solution set is established and then a selection operator is designed that complies with the performance indicator.

Binary Classification Classification +5

Image Understanding from Experts' Eyes by Modeling Perceptual Skill of Diagnostic Reasoning Processes

no code implementations CVPR 2013 Rui Li, Pengcheng Shi, Anne R. Haake

Eliciting and representing experts' remarkable perceptual capability of locating, identifying and categorizing objects in images specific to their domains of expertise will benefit image understanding in terms of transferring human domain knowledge and perceptual expertise into image-based computational procedures.

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