Linwei Ye

1.5k citations

27 papers · 836 indexed · 1 hit paper · h-index 12

Impact in

Computer Vision and Pattern Recognition top 1%
- Visual Attention and Saliency Detection
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
- Image and Video Quality Assessment
- Video Surveillance and Tracking Methods
Sensory Systems top 5%
- Olfactory and Sensory Function Studies

Papers in ⓘ

Computer Vision and Pattern Recognition 24
- Visual Attention and Saliency Detection 11
- Advanced Image and Video Retrieval Techniques 9
- Advanced Neural Network Applications 8
- Image Enhancement Techniques 4
- Multimodal Machine Learning Applications 3
Sensory Systems 4
- Olfactory and Sensory Function Studies 4

Co-authors: Zhi Liu (20 shared papers)Mrigank Rochan (2 shared papers)Yang Wang (4 shared papers)Liquan Shen (4 shared papers)Guangling Sun (2 shared papers)Yang Wang (6 shared papers)Junhao Li (1 shared paper)Xiaofei Zhou (4 shared papers)
Journals: Neurocomputing (4 papers)IEEE Signal Processing Letters (3 papers)Image and Vision Computing (2 papers)Journal of Visual Communication and Image Representation (2 papers)IEEE Transactions on Circuits and Systems for Video Technology (2 papers)
Partner nations: China Canada United States

In The Last Decade

Linwei Ye

26 papers receiving 823 citations

Hit Papers

align trajectories log scale

Cross-Modal Self-Attention Network for Referring Image Segmentation 2019 · 329 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2019 Cross-Modal Self-Attention Network for Referring Image Segmentation

Peers

Countries citing papers authored by Linwei Ye

Since Specialization

Citations

This map shows the geographic impact of Linwei Ye's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Linwei Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Linwei Ye more than expected).

Fields of papers citing papers by Linwei Ye

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Linwei Ye. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Linwei Ye. The network helps show where Linwei Ye may publish in the future.

Co-authors

The 25 scholars most cited alongside Linwei Ye, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Linwei Ye Line = papers co-authored together Linwei Ye links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Cross-Modal Self-Attention Network for Referring Image Segmentation Linwei Ye, Mrigank Rochan, Zhi Liu, Yang Wang Hit paper breakdown →	2019	329
2	Saliency Detection for Unconstrained Videos Using Superpixel-Level Graph and Spatiotemporal Propagation IEEE Transactions on Circuits and Systems for Video Technology ·Zhi Liu, Junhao Li, Linwei Ye, Guangling Sun, Liquan Shen	2016	141
3	Salient Object Segmentation via Effective Integration of Saliency and Objectness IEEE Transactions on Multimedia ·Linwei Ye, Zhi Liu, Lina Li, Liquan Shen, Cong Bai, Yang Wang	2017	69
4	Referring Segmentation in Images and Videos with Cross-Modal Self-Attention Network IEEE Transactions on Pattern Analysis and Machine Intelligence ·Linwei Ye, Mrigank Rochan, Zhi Liu, Xiaoqin Zhang, Yang Wang	2021	69
5	Co-Saliency Detection via Co-Salient Object Discovery and Recovery IEEE Signal Processing Letters ·Linwei Ye, Zhi Liu, Junhao Li, Wan‐Lei Zhao, Liquan Shen	2015	47
6	Improving Saliency Detection Via Multiple Kernel Boosting and Adaptive Fusion IEEE Signal Processing Letters ·Xiaofei Zhou, Zhi Liu, Guangling Sun, Linwei Ye, Xiangyang Wang	2016	39
7	Saliency detection via multi-level integration and multi-scale fusion neural networks Neurocomputing ·Mengke Huang, Zhi Liu, Linwei Ye, Xiaofei Zhou, Yang Wang	2019	24
8	Attentional coarse-and-fine generative adversarial networks for image inpainting Neurocomputing ·Minyu Chen, Zhi Liu, Linwei Ye, Yang Wang	2020	20
9	Region-of-interest and channel attention-based joint optimization of image compression and computer vision Neurocomputing ·Binglin Li, Linwei Ye, Jie Liang, Yang Wang, Jingning Han	2022	16
10	Circular Complement Network for RGB-D Salient Object Detection Neurocomputing ·Zhen Bai, Zhi Liu, Gongyang Li, Linwei Ye, Yang Wang	2021	12
11	Few-shot personalized saliency prediction using meta-learning Image and Vision Computing ·Xinhui Luo, Zhi Liu, Weijie Wei, Linwei Ye, Tianhong Zhang, Lihua Xu, Jijun Wang	2022	11
12	Depth-aware object instance segmentation Linwei Ye, Zhi Liu, Yang Wang	2017	11
13	Saliency Detection Via Similar Image Retrieval IEEE Signal Processing Letters ·Linwei Ye, Zhi Liu, Xiaofei Zhou, Liquan Shen, Jian Zhang	2016	7
14	Learning Semantic Segmentation with Diverse Supervision Linwei Ye, Zhi Liu, Yang Wang	2018	7
15	Privacy-Preserving Age Estimation for Content Rating Linwei Ye, Binglin Li, Noman Mohammed, Yang Wang, Jie Liang	2018	6
16	ATCC: Accurate tracking by criss-cross location attention Image and Vision Computing ·Yong Wu, Zhi Liu, Xiaofei Zhou, Linwei Ye, Yang Wang	2021	4
17	Weakly labeled fine-grained classification with hierarchy relationship of fine and coarse labels Journal of Visual Communication and Image Representation ·Qihan Jiao, Zhi Liu, Linwei Ye, Yang Wang	2019	4
18	Weakly supervised instance segmentation using multi-stage erasing refinement and saliency-guided proposals ordering Journal of Visual Communication and Image Representation ·Zheng Hu, Zhi Liu, Gongyang Li, Linwei Ye, Lei Zhou, Yang Wang	2020	4
19	VELIE: A Vehicle-Based Efficient Low-Light Image Enhancement Method for Intelligent Vehicles Sensors ·Linwei Ye, Dong Wang, Dongyi Yang, Zhiyuan Ma, Quan Zhang	2024	3
20	Evaluation on fusion of saliency and objectness for salient object segmentation Linwei Ye, Zhi Liu, Lina Li	2015	3

About Linwei Ye

Linwei Ye is a scholar working on Computer Vision and Pattern Recognition, Sensory Systems, Business and International Management, Human-Computer Interaction and Media Technology, having authored 27 papers that have together received 836 indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (11 papers), Advanced Image and Video Retrieval Techniques (9 papers), Advanced Neural Network Applications (8 papers), Olfactory and Sensory Function Studies (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Image Enhancement Techniques (4 papers), Multimodal Machine Learning Applications (3 papers) and Advanced Image Fusion Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (733 citations), Sensory Systems (92 citations), Media Technology (79 citations), Human-Computer Interaction (35 citations) and Artificial Intelligence (167 citations). Linwei Ye has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Zhi Liu, Mrigank Rochan, Yang Wang, Liquan Shen, Guangling Sun, Yang Wang, Junhao Li, Xiaofei Zhou, Xiaoqin Zhang and Lina Li. Their work appears in journals such as Neurocomputing, IEEE Signal Processing Letters, Image and Vision Computing, Journal of Visual Communication and Image Representation and IEEE Transactions on Circuits and Systems for Video Technology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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