About Me

I’m now a first-year PhD student in computer science at the University of Maryland (College Park), working with Prof. Matthias Zwicker. Before that, I got my master’s degree in Data Science and Information Technology at TBSI, Tsinghua University(THU), supervised by Prof. Lu Fang and Prof. Qionghai Dai. Prior to that, I spent wonderful 4 years at Sun Yat-Sen University(SYSU), and obtained my bachelor’s degree in 2021.

My research interests mainly lie in 3D computer vision, especially in:

• 3D Representation: Geometric Primitive based 3D Modeling (such as Quadrics and CAD)
• 3D Reconstruction: Semantic-aware Reconstruction and Rendering from images and video
• 3D Understanding: Hierarchical 3D Scene Parsing and Navigation

My goal is to model, reconstruct, and manipuate the 3D world in a more efficient and interpretable manner.

News

• [Feb. 2024] Our paper OmniSeg3D is accepted by CVPR 2024 and code is available now!
• [July. 2023] Our paper PARF is accepted by ICCV 2023!
• [July. 2022] Our paper ParseMVS is accepted by ACM MM 2022!

Publications

	OmniSeg3D: Omniversal 3D Segmentation via Hierarchical Contrastive Learning Haiyang Ying, Yixuan Yin, Jinzhi Zhang, Fan Wang, Tao Yu, Ruqi Huang, Fu Fang† (CVPR 2024) [ArXiv] [Project Page] [Code]
	PARF: Primitive-Aware Radiance Fusion for Indoor Scene Novel View Synthesis Haiyang Ying, Baowei Jiang, Jinzhi Zhang, Di Xu, Tao Yu†, Qionghai Dai, Fu Fang† The International Conference on Computer Vision (ICCV) 2023 [ArXiv] [Paper] [Project Page] [Code(coming soon)]
	ParseMVS: Learning Primitive-aware Surface Representations for Sparse Multi-view Stereopsis Haiyang Ying*, Jinzhi Zhang*, Yuzhe Chen, Zheng Cao, Jing Xiao, Ruqi Huang†, Fu Fang† The 30th ACM International Conference on Multimedia (ACM MM 2022) [Paper][Code]

Research Experiences

• Semantic-Aware Indoor Scene Reconstruction and Rendering Sep. 2022 – May. 2023 Propose a semantic-aware hybrid representation for indoor scene modeling.
  Design a framework for fast indoor scene reconstruction and rendering with RGB-D input.
  Implement the proposed framework based on Instant-NGP to achieve higher-quality rendering.
  Mentor: Prof. Lu Fang and Tao Yu

• Semantic-Aware Sparse View 3D Reconstruction Sep. 2021 – Aug. 2022
  Propose a semantic-based representation to encode geometry, texture, and visibility on primitives.
  Design a pipeline for multi-view 3D reconstruction under sparse observations.
  Explore the capacity of implicit function for local representation and optimization.
  Mentor: Prof. Lu Fang and Prof. Ruqi Huang

• Dynamic Vascular 3D Reconstruction (B.S. Thesis) Oct. 2020 – Aug. 2021
  Propose to model 3D dynamic tissue with implicit representation.
  Design a pipeline for 3D reconstruction with multi-view cone beam CT images.
  Mentor: Prof. Lu Fang

Education

• Ph.D. student, Computer Science
  Sept. 2024 - Present, University of Maryland (College Park), US.
• M.Phil., Data Science and Information Technology
  Sept. 2021 - Jun. 2024, Tsinghua University, China.
• B.Eng., Electronic Information Science and Technology
  Sept. 2017 - Jun. 2021, Sun Yat-Sen University, China.

Honors & Awards

• 2021, Excellent Graduate, Sun Yat-Sen University.
• 2019, 2020, National Scholarship, the Minister of Education, China.
• 2018, 1nd Prize, College Electronic Design Competition, Guangdong, China.
• 2018, 2019, 2020, Excellence Student the 1st-class Scholarship, Sun Yat-Sen University.
• 2018, AEON Scholarship, Sun Yat-Sen University.

Teaching Experiences

• Fall 2022, Teaching Assistant, Tsinghua University.
  Course: Media and Cognition (English)

• Fall 2023, Teaching Assistant, Tsinghua University.
  Course: Machine Vision (English)