Yuanzhi Liang

liangyzh18 [at] outlook [dot] com

About Me

I am currently a Ph.D. student at the University of Technology Sydney, advised by Dr. Linchao Zhu and Prof. Yi Yang. I received a Master's degree from Xi’an Jiaotong Univerisity in 2020. I was a member of the SMILES LAB, advised by Prof. Xueming Qian and Prof. Li Zhu.

My academic and professional journey has been driven by two kinds of curiosities: the development of machines capable of perceiving real-world scenarios and understanding semantics.

My primary research interests include:
1. Visual Perception in Real-world Scenarios: Tackling the challenges of visual perception in real-world scenarios and exploring their relevant applications.
2. Multi-modal Representation Learning: Investigating representation learning for multi-modal data, with a special focus on visual-language tasks.

Lately, my research trajectory has evolved:
1. Perception in Interactive Environments: I'm delving deeper into addressing perception challenges in interactive settings. A significant portion of this line is dedicated to improving the capabilities of robotic systems, enabling them to interpret and interact seamlessly within real-world environments.
2. Development of Humanoid AI Agents Using Large Models: I'm captivated by the possibilities large models offer in the creation of humanoid AI agents. The overarching objective is to mimic human-like intelligence and behavioral patterns more closely.

Work Experience

  • Jul 2021 - Dec 2021, Alibaba DAMO Academy
    • Research intern working on virtual human synthesis.

  • Jul 2020 - Jul 2021, Baidu Research
    • Research intern working on visual knowledge embedding, object recognition, and multi-modal representation.

  • Mar 2020 - Jun 2020, JD AI Research
    • Research intern working on product recognition.

  • Aug 2018 - Jun 2019, JD AI Research
    • Research intern working on visual-language representation learning.

Selected Honors

  • First place in AliProducts Challenge @ CVPR 2020 the RetailVision workshop.
  • First place in iMat Product Competition @ CVPR 2019 FGVC6 workshop.
  • First place in in Fieldguide Challenge: Moths & Butterflies @ CVPR 2019 FGVC6 workshop.
  • Second place in iFood Competition @ CVPR 2019 FGVC6 workshop.
  • Second place in iMet2020 Fine-grained Attributes Classification Competition @ CVPR 2020 FGVC7 workshop.
  • Kaggle Silver Medal in Deepfake Detection Challenge 2020.

Selected Publications

  • MAAL: Multimodality-Aware Autoencoder-based Affordance Learning for 3D Articulated Objects.
    Yuanzhi Liang, Xiaohan Wang, Linchao Zhu, Yi Yang.
    Accepted by ICCV 2023

  • A Simple Episodic Linear Probe Improves Visual Recognition in the Wild.
    Yuanzhi Liang, Linchao Zhu, Xiaohan Wang, Yi Yang.
    Accepted by CVPR 2022 (Score 1/2/2)

  • SEEG: Semantic Energized Co-speech Gesture Generation.
    Yuanzhi Liang, Qianyu Feng, Linchao Zhu, Li Hu, Pan Pan, Yi Yang.
    Accepted by CVPR 2022

  • VrR-VG: Refocusing Visually-Relevant Relationships.
    Yuanzhi Liang, Yalong Bai, Wei Zhang, Xueming Qian, Li Zhu, Tao Mei.
    Accepted by ICCV 2019

  • IcoCap: Improving Video Captioning by Compounding Images.
    Yuanzhi Liang, Linchao Zhu, Xiaohan Wang, Yi Yang.
    Accepted by TMM 2023

  • Penalizing the Hard Example But Not Too Much: A Strong Baseline for Fine-Grained Visual Classification.
    Yuanzhi Liang, Linchao Zhu, Xiaohan Wang, Yi Yang.
    Accepted by TNNLS 2022

  • Towards Better Railway Service: Passengers Counting in Railway Compartment.
    Yuanzhi Liang, Zhu Li, Xueming Qian.
    Accepted by TCSVT 2020

  • Tachikuma: Understading Complex Interactions with Multi-Character and Novel Objects by Large Language Models.
    Yuanzhi Liang, Linchao Zhu, Yi Yang.
    Ongoing work on arXiv

  • Removing Raindrops and Rain Streaks in One Go.
    Ruijie Quan, Xin Yu, Yuanzhi Liang, Yi Yang.
    Accepted by CVPR 2021

  • Product Recognition for Unmanned Vending Machines.
    Chengxu Liu, Zongyang Da, Yuanzhi Liang, Yao Xue, Guoshuai Zhao, Xueming Qian.
    Accepted by TNNLS 2022

  • Food and Ingredient Joint Learning for Fine-Grained Recognition.
    Chengxu Liu, Yuanzhi Liang, Yao Xue, Xueming Qian, Jianlong Fu.
    Accepted by TCSVT 2020

    • Academic Services

  • Reviewer for TPAMI, TIP, ICCV, CVPR, ECCV, MM, ICME, KBS and CAAI.