Xi Tian (田希)

Dr. Xi received his PhD in 2024 from the University of Bath, UK, under the supervision of Dr. Yong-Liang Yang. He specialized in multimodal deep learning applications in computer vision, with a focus on text-guided image and 3D shape generation. He earned his MSc in Machine Learning from the University of Bristol in 2016, and his BSc in Computer Science from Beijing University of Posts and Telecommunications in 2014. His professional experience includes working with large language models and deploying deep learning techniques in medical image processing.

News

Jan, 2024	Successfully defended my PhD dissertation.
Jul, 2023	One paper on the text-to-shape task was accepted at the 2023 IEEE International Conference on Computer Vision (ICCV).
Nov, 2022	One paper on text-to-storyboard retrieval accepted by the Computer Vision and Media Journal (CVMJ).
Oct, 2022	One paper on layout-to-image generation was presented at the 2022 British Machine Vision Conference (BMVC).

Selected Publications

Script-to-storyboard: A new contextual retrieval dataset and benchmark

Xi Tian, Yong-Liang Yang, and Qi Wu

Computational Visual Media, 2025

Bib HTML PDF

@article{tian2025script,
  title = {Script-to-storyboard: A new contextual retrieval dataset and benchmark},
  author = {Tian, Xi and Yang, Yong-Liang and Wu, Qi},
  journal = {Computational Visual Media},
  volume = {11},
  number = {1},
  pages = {103--122},
  year = {2025},
  publisher = {TUP},
}

ShapeScaffolder: Structure-Aware 3D Shape Generation from Text

Xi Tian, Yong-Liang Yang, and Qi Wu

Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), Oct 2023

Bib HTML PDF

@article{Tian_2023_ICCV,
  author = {Tian, Xi and Yang, Yong-Liang and Wu, Qi},
  title = {ShapeScaffolder: Structure-Aware 3D Shape Generation from Text},
  journal = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
  month = oct,
  year = {2023},
  pages = {2715-2724},
}

Enhancing Person Synthesis in Complex Scenes via Intrinsic and Contextual Structure Modeling

Xi Tian, Yongliang Yang, and Qi Wu

33st British Machine Vision Conference (BMVC), Oct 2022

Bib HTML PDF

@article{tian2022enhancing,
  title = {Enhancing Person Synthesis in Complex Scenes via Intrinsic and Contextual Structure Modeling},
  author = {Tian, Xi and Yang, Yongliang and Wu, Qi},
  year = {2022},
  journal = {33st British Machine Vision Conference (BMVC)},
  publisher = {BMVA Press},
}

3D DenseNet deep learning based preoperative Computed Tomography for detecting myasthenia gravis in patients with thymoma

Zhenguo Liu, Ying Zhu, Yujie Yuan, and 8 more authors

Frontiers in Oncology, Oct 2021

Bib HTML

@article{liu20213d,
  title = {3D DenseNet deep learning based preoperative Computed Tomography for detecting myasthenia gravis in patients with thymoma},
  author = {Liu, Zhenguo and Zhu, Ying and Yuan, Yujie and Yang, Lei and Wang, Kefeng and Wang, Minghui and Yang, Xiaoyu and Wu, Xi and Tian, Xi and Zhang, Rongguo and others},
  journal = {Frontiers in Oncology},
  volume = {11},
  pages = {631964},
  year = {2021},
  publisher = {Frontiers Media SA},
}

Deep residual nets model for staging liver fibrosis on plain CT images

Qiuju Li, Bing Yu, Xi Tian, and 3 more authors

International Journal of Computer Assisted Radiology and Surgery, Oct 2020

Bib HTML

@article{li2020deep,
  title = {Deep residual nets model for staging liver fibrosis on plain CT images},
  author = {Li, Qiuju and Yu, Bing and Tian, Xi and Cui, Xing and Zhang, Rongguo and Guo, Qiyong},
  journal = {International Journal of Computer Assisted Radiology and Surgery},
  volume = {15},
  pages = {1399--1406},
  year = {2020},
  publisher = {Springer},
}

A CT-derived deep neural network predicts for programmed death ligand-1 expression status in advanced lung adenocarcinomas

Ying Zhu, Yang-Li Liu, Yu Feng, and 8 more authors

Annals of Translational Medicine, Oct 2020

Bib HTML

@article{zhu2020ct,
  title = {A CT-derived deep neural network predicts for programmed death ligand-1 expression status in advanced lung adenocarcinomas},
  author = {Zhu, Ying and Liu, Yang-Li and Feng, Yu and Yang, Xiao-Yu and Zhang, Jing and Chang, Dan-Dan and Wu, Xi and Tian, Xi and Tang, Ke-Jing and Xie, Can-Mao and others},
  journal = {Annals of Translational Medicine},
  volume = {8},
  number = {15},
  year = {2020},
  publisher = {AME Publications},
}

Survey on deep learning for pulmonary medical imaging

Jiechao Ma, Yang Song, Xi Tian, and 3 more authors

Frontiers of medicine, Oct 2020

Bib HTML

@article{ma2020survey,
  title = {Survey on deep learning for pulmonary medical imaging},
  author = {Ma, Jiechao and Song, Yang and Tian, Xi and Hua, Yiting and Zhang, Rongguo and Wu, Jianlin},
  journal = {Frontiers of medicine},
  volume = {14},
  pages = {450--469},
  year = {2020},
  publisher = {Springer},
}

Development of a deep learning model for classifying thymoma as Masaoka-Koga stage I or II via preoperative CT images

Lei Yang, Wenjia Cai, Xiaoyu Yang, and 8 more authors

Annals of Translational Medicine, Oct 2020

Bib HTML

@article{yang2020development,
  title = {Development of a deep learning model for classifying thymoma as Masaoka-Koga stage I or II via preoperative CT images},
  author = {Yang, Lei and Cai, Wenjia and Yang, Xiaoyu and Zhu, Haoshuai and Liu, Zhenguo and Wu, Xi and Lei, Yiyan and Zou, Jianyong and Zeng, Bo and Tian, Xi and others},
  journal = {Annals of Translational Medicine},
  volume = {8},
  number = {6},
  year = {2020},
  publisher = {AME Publications},
}