World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
6009
World Ranking
11197
National Ranking
1373

Overview

Ying Shan is affiliated with Tencent (China), based in China, and specializes primarily in computer science with a focus on computer vision and related subfields. Their research encompasses areas such as computer vision and pattern recognition, artificial intelligence, signal processing, computational mechanics, and computer graphics and computer-aided design.

Their main research topics include multimodal machine learning applications, generative adversarial networks and image synthesis, advanced vision and imaging, advanced image and video retrieval techniques, human pose and action recognition, video analysis and summarization, and advanced image processing techniques.

Ying Shan has multiple frequent collaborators including Yixiao Ge, Xintao Wang, Yan-Pei Cao, Zhongang Qi, and Xiaodong Cun. Their work has been published extensively, with many contributions to venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Circuits and Systems for Video Technology
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • SSRN Electronic Journal

Recent notable papers authored or co-authored by Ying Shan include:

  • T2I-Adapter: Learning Adapters to Dig Out More Controllable Ability for Text-to-Image Diffusion Models, 2024, Proceedings of the AAAI Conference on Artificial Intelligence
  • UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Bridging Video-text Retrieval with Multiple Choice Questions, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Crossover Learning for Fast Online Video Instance Segmentation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data, 2021, arXiv (Cornell University)

Best Publications

  • Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

    Xintao Wang;Liangbin Xie;Chao Dong;Ying Shan

  • Towards Real-World Blind Face Restoration with Generative Facial Prior

    Xintao Wang;Yu Li;Honglun Zhang;Ying Shan

  • Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features

    Ying Shan;T. Ryan Hoens;Jian Jiao;Haijing Wang

  • Expressive expression mapping with ratio images

    Zicheng Liu;Ying Shan;Zhengyou Zhang

  • Visual panel: virtual mouse, keyboard and 3D controller with an ordinary piece of paper

    Zhengyou Zhang;Ying Wu;Ying Shan;Steven Shafer

  • Model-based bundle adjustment with application to face modeling

    Ying Shan;Zicheng Liu;Zhengyou Zhang

  • System and method for providing a mobile input device

    Zhengyou Zhang;Ying Shan;Steven A. N. Shafer;Ying Wu

  • Robust and Rapid Generation of Animated Faces from Video Images: A Model-Based Modeling Approach

    Zhengyou Zhang;Zicheng Liu;Dennis Adler;Michael F. Cohen

  • Rapid object indexing using locality sensitive hashing and joint 3D-signature space estimation

    B. Matei;Ying Shan;H.S. Sawhney;Yi Tan

  • Fast Video Object Segmentation Using the Global Context Module

    Yu Li;Zhuoran Shen;Ying Shan

  • System and method for transforming an ordinary computer monitor into a touch screen

    Zhengyou Zhang;Ying Shan

  • Open-book Video Captioning with Retrieve-Copy-Generate Network

    Ziqi Zhang;Zhongang Qi;Chunfeng Yuan;Ying Shan

  • Unsupervised Learning of Discriminative Edge Measures for Vehicle Matching between Nonoverlapping Cameras

    Ying Shan;H.S. Sawhney;R. Kumar

  • Incremental motion estimation through local bundle adjustment

    Zhengyou Zhang;Ying Shan

  • System and method for progressive stereo matching of digital images

    Zhengyou Zhang;Ying Shan

  • Cross-modal Consensus Network for Weakly Supervised Temporal Action Localization

    Fa-Ting Hong;Jia-Chang Feng;Dan Xu;Ying Shan

  • Crossover Learning for Fast Online Video Instance Segmentation

    Shusheng Yang;Yuxin Fang;Xinggang Wang;Yu Li

  • Sub-pixel location of edges with non-uniform blurring: a finite closed-form approach

    Y. Shan;G.W. Boon

  • System and method for detecting still objects in images

    Feng Han;Ying Shan;Ryan Cekander;Harpreet S. Sawhney

  • Method and apparatus for tracking a movable object

    Yanlin Guo;Harpreet Sawhney;Rakesh Kumar;Ying Shan

  • A Progressive Scheme for Stereo Matching

    Zhengyou Zhang;Ying Shan

  • Object modeling system and process employing noise elimination and robust surface extraction techniques

    Zhengyou Zhang;Charles Loop;Ying Shan

Frequent Co-Authors

Zhengyou Zhang
Zhengyou Zhang Tencent (China)
Harpreet Sawhney
Harpreet Sawhney Microsoft (United States)
Rakesh Kumar
Rakesh Kumar SRI International
Zicheng Liu
Zicheng Liu Microsoft (United States)
Jianchang Mao
Jianchang Mao Google (United States)
Xinggang Wang
Xinggang Wang Huazhong University of Science and Technology
Wenyu Liu
Wenyu Liu Huazhong University of Science and Technology
Dong Yu
Dong Yu Tencent (China)
Ying Wu
Ying Wu Northwestern University
Chao Dong
Chao Dong Shenzhen Institutes of Advanced Technology

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