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D-Index & Metrics

Computer Science

D-Index
49
Citations
9401
World Ranking
5905
National Ranking
785

Overview

Lianli Gao is a researcher affiliated with the University of Electronic Science and Technology of China. Their primary field of study is Computer Science, with a specialized focus on Computer Vision and Pattern Recognition, Artificial Intelligence, and Signal Processing. They have contributed extensively to advanced topics within these fields, including Multimodal Machine Learning Applications and Advanced Image and Video Retrieval Techniques.

Their research portfolio contains a significant number of publications, particularly in notable venues such as arXiv (Cornell University), IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Multimedia, IEEE Transactions on Image Processing, and the journal Pattern Recognition.

Frequent coauthors collaborating with Lianli Gao include Jingkuan Song, Heng Tao Shen, Pengpeng Zeng, Xinyu Lyu, and Yuan-Fang Li, reflecting a broad network of scientific partnerships.

Some of their recent publications are:

  • "Hierarchical Representation Network With Auxiliary Tasks for Video Captioning and Video Question Answering" (2021) published in IEEE Transactions on Image Processing
  • "From General to Specific: Informative Scene Graph Generation via Balance Adjustment" (2021) presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Rich Visual Knowledge-Based Augmentation Network for Visual Question Answering" (2020) featured in IEEE Transactions on Neural Networks and Learning Systems
  • "S2 Transformer for Image Captioning" (2022) at the Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
  • "Unified Binary Generative Adversarial Network for Image Retrieval and Compression" (2020) published in the International Journal of Computer Vision

Their research encompasses multiple subfields, including Human Pose and Action Recognition, Anomaly Detection Techniques and Applications, Advanced Neural Network Applications, and Adversarial Robustness in Machine Learning. These areas indicate a focus not only on image and video analysis but also on machine learning robustness and applications to broader vision tasks.

Best Publications

  • Video Captioning With Attention-Based LSTM and Semantic Consistency

    Lianli Gao;Zhao Guo;Hanwang Zhang;Xing Xu

  • Beyond Product Quantization: Deep Progressive Quantization for Image Retrieval

    Lianli Gao;Xiaosu Zhu;Jingkuan Song;Zhou Zhao

  • Beyond Frame-level CNN: Saliency-Aware 3-D CNN With LSTM for Video Action Recognition

    Xuanhan Wang;Lianli Gao;Jingkuan Song;Heng Tao Shen

  • Self-Supervised Video Hashing With Hierarchical Binary Auto-Encoder

    Jingkuan Song;Hanwang Zhang;Xiangpeng Li;Lianli Gao

  • Neighbourhood Watch: Referring Expression Comprehension via Language-Guided Graph Attention Networks

    Peng Wang;Qi Wu;Jiewei Cao;Chunhua Shen

  • Two-Stream 3-D convNet Fusion for Action Recognition in Videos With Arbitrary Size and Length

    Xuanhan Wang;Lianli Gao;Peng Wang;Xiaoshuai Sun

  • From Deterministic to Generative: Multimodal Stochastic RNNs for Video Captioning

    Jingkuan Song;Yuyu Guo;Lianli Gao;Xuelong Li

  • Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering

    Xiangpeng Li;Jingkuan Song;Lianli Gao;Xianglong Liu

  • Quantization-based hashing

    Jingkuan Song;Lianli Gao;Li Liu;Xiaofeng Zhu

  • Hierarchical LSTMs with Adaptive Attention for Visual Captioning

    Lianli Gao;Xiangpeng Li;Jingkuan Song;Heng Tao Shen

  • Deep adversarial metric learning for cross-modal retrieval

    Xing Xu;Li He;Huimin Lu;Lianli Gao

  • Hierarchical LSTM with Adjusted Temporal Attention for Video Captioning

    Jingkuan Song;Lianli Gao;Zhao Guo;Wu Liu

  • Love thy neighbour: automatic animal behavioural classification of acceleration data using the K-nearest neighbour algorithm.

    Owen R. Bidder;Hamish A. Campbell;Agustina Gómez-Laich;Patricia Urgé

  • Template-Based Math Word Problem Solvers with Recursive Neural Networks.

    Lei Wang;Dongxiang Zhang;Jipeng Zhang;Xing Xu

  • Learning in high-dimensional multimedia data: the state of the art

    Lianli Gao;Jingkuan Song;Xingyi Liu;Junming Shao

  • Optimized Graph Learning Using Partial Tags and Multiple Features for Image and Video Annotation

    Jingkuan Song;Lianli Gao;Feiping Nie;Heng Tao Shen

  • MathDQN: Solving Arithmetic Word Problems via Deep Reinforcement Learning.

    Lei Wang;Dongxiang Zhang;Lianli Gao;Jingkuan Song

  • Binary Generative Adversarial Networks for Image Retrieval

    Jingkuan Song;Tao He;Lianli Gao;Xing Xu

  • Matching User with Item Set: Collaborative Bundle Recommendation with Deep Attention Network

    Liang Chen;Yang Liu;Xiangnan He;Lianli Gao

  • Patch-Wise Attack for Fooling Deep Neural Network

    Lianli Gao;Qilong Zhang;Jingkuan Song;Xianglong Liu

  • Hierarchical LSTM with Adjusted Temporal Attention for Video Captioning

    Jingkuan Song;Zhao Guo;Lianli Gao;Wu Liu

  • Hierarchical LSTMs with Adaptive Attention for Visual Captioning

    Jingkuan Song;Xiangpeng Li;Lianli Gao;Heng Tao Shen

Frequent Co-Authors

Jingkuan Song
Jingkuan Song Columbia University
Heng Tao Shen
Heng Tao Shen University of Electronic Science and Technology of China
Fumin Shen
Fumin Shen University of Electronic Science and Technology of China
Dongxiang Zhang
Dongxiang Zhang Zhejiang University
Jane Hunter
Jane Hunter University of Technology Sydney
Nicu Sebe
Nicu Sebe University of Trento
Xianglong Liu
Xianglong Liu Beihang University
Zhou Zhao
Zhou Zhao Zhejiang University
Xuelong Li
Xuelong Li China Telecom (China)
Alan Hanjalic
Alan Hanjalic Delft University of Technology

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