I am a Computer Science PhD Candidate at UIUC. My PhD advisor is Prof. Shenlong Wang. I am widely interested in topics related to 3D generative modeling in computer vision. My past and ongoing projects involve scene-level generation, editing, 3D representation and 3D-related downstream application.
During my Phd, I am fortunate to collaborate with David Forsyth, Katie Driggs-Campbell, Wei-chiu Ma, Duygu Ceylan, Niloy Mitra, Anna Frühstück, Zexiang Xu, Paul Guerrero, Chuhang Zou, Xiaohan Fei, Bryan A. Plummer, Shengze Wang and many other amazing researchers.
Previously, I completed my Bachelor's degree with the highest honor at UIUC, with a major in Computer Science and minor in Mathematics. I was a research assistant at the Data-Driven Design group, led by Prof. Ranjitha Kumar. My undergrad research focused on fashion AI.
I am co-organizing the external speaker seminar at UIUC vision group. If you are interested in presenting, please let me know!
Inspired by Wei-chiu Ma, I have decided to commit 1~2 hours every week to provide guidance, suggestions, and/or mentorships for students from underrepresented groups or whoever is in need. Please fill in this form if you are interested.
E-Mail | Github | LinkedIn | CV | Google Scholar
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Sept 2023 |
Our paper, "Sim-on-Wheels: Physical World in the Loop Simulation for Self-Driving", is accepted for publication in the IEEE Robotics and Automation
Letters (RA-L). |
Aug 2023 |
Intern at Adobe as Research Scientist in San Jose, CA |
May 2023 |
Intern at Amazon as Applied Scientist in Bellevue, WA |
October 2022 |
Our paper, "To Explain or Not to Explain: A Study on the Necessity of Explanations for Autonomous Vehicles", won Best Paper Award at NeurIPS 2022 Progress and Challenges in Building Trustworthy Embodied AI Workshop (TEA 2022). |
October 2022 |
Our paper, "To Explain or Not to Explain: A Study on the Necessity of Explanations for Autonomous Vehicles", is accepted at NeurIPS 2022 Progress and Challenges in Building Trustworthy Embodied AI Workshop (TEA 2022). |
September 2022 |
Our paper, "SGAM: Building a Virtual 3D World through Simultaneous Generation and Mapping", is accepted at NeurIPS 2022. |
June 2022 |
Our paper, "CoCAtt: A Cognitive-Conditioned Driver Attention Dataset", is accepted at ITSC 2022. |
November 2021 |
Passed my PhD Qualifying Exam! Very excited to be admitted to PhD Candidancy at UIUC! |
July 2021 |
Our paper, "Effectively Leveraging Attributes for Visual Similarity", is accepted at International Conference on Computer Vision, ICCV 2021. |
April 2021 |
Our peer-reviewed workshop paper, "Effectively Leveraging Attributes for Visual Similarity", is accepted at Fourth Workshop on Computer Vision for Fashion, Art and Design at CVPR 2021. |
March 2021 |
Our peer-reviewed extended abstract, "AutoPreview: A Framework for Autopilot Behavior Understanding", is accepted at CHI2021 Late Breaking Work (Acceptance Rate: 39%). |
Jan 2021 |
Our peer-reviewed extended abstract, "Building Mental Models through Preview of Autopilot Behaviors", is accepted at TRAITS workshop at HRI2021. |
March 2020 |
Our workshop Paper, "Can AI decrypt fashion jargon for you?", is accepted at AI4HCI workshop at CHI 2020. |
June 2019 |
Intern at Reconstruct Inc. |
May 2019 |
Graduated with highest honor in UIUC. |
April 2019 |
Accepted CS PhD offer at UIUC and joined Data Driven Design group led by Prof. Kumar. |
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Sim-on-Wheels: Physical World in the Loop Simulation for Self-Driving
Yuan Shen*, Bhargav Chandaka*, Zhi-hao Lin, Albert Zhai, Hang Cui, David Forsyth, and Shenlong Wang
IEEE Robotics and Automation Letters (RA-L)
project | paper | codebase
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SGAM: Building a Virtual 3D World through Simultaneous Generation and Mapping
Yuan Shen, Wei-Chiu Ma, Shenlong Wang
Thirty-sixth Conference on Neural Information Processing Systems. (NeurIPS 2022) (Acceptance Rate: 25.6%)
project | paper | poster | video | codebase | colab quickstart
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To Explain or Not to Explain: A Study on the Necessity of Explanations for Autonomous Vehicles
Yuan Shen, Shanduojiao Jiang, Yanlin Chen, Eileen Yang, Xilun Jin, Yuliang Fan, Katie Driggs-Campbell
Best Paper Award at NeurIPS 2022 Progress and Challenges in Building Trustworthy Embodied AI Workshop (TEA 2022)
paper | poster | video | dataset
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CoCAtt: A Cognitive-Conditioned Driver Attention Dataset
Yuan Shen, Niviru Wijayaratne & Pranav Sriram, Aamir Hasan, Peter Du and Katherine Driggs-Campbell
The 25th IEEE International Conference on Intelligent Transportation Systems. (ITSC 2022)
project | paper | dataset
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Effectively Using Attributes for Visual Similarity
Samarth Mishra, Zhongping Zhang, Yuan Shen, Ranjitha Kumar, Venkatesh Saligrama, Bryan Plummer
International Conference on Computer Vision (IEEE). (ICCV 2021)
Conference on Computer Vision and Pattern Recognition Workshop (IEEE). (CVPRW 2021)
paper
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AutoPreview: A Framework for Autopilot Behavior Understanding
Yuan Shen, Niviru Wijayaratne, Peter Du, Shanduojiao Jiang, Katherine Driggs Campbell
SIGCHI Conference on Human Factors in Computing Systems (CHI 2021) Late Breaking Work (Acceptance Rate: 39%)
paper
The Road to a successful HRI: AI, Trust and ethicS (TRAITS) Workshop at ACM/IEEE International Conference on Human-Robot Interaction (HRI 2021)
paper
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