Seo Yeon (Karen)  Chung

Seo Yeon (Karen) Chung

Scholar Title

Undergraduate Research and Innovation Scholar

Research Title

Fast Object Detection and Localization via Probabilistic Inverse Graphics




Electrical Engineering and Computer Science

Research Areas
  • Computer Graphics and Vision

Vikash Kumar Mansinghka


A striking feature of human vision is our ability to learn a model of a novel object from just a single image and then robustly detect and localize instances of that object in 3D scenes. In my SuperUROP project, I aim to develop a vision system capable of this type of efficient model learning and fast object detection and localization. My approach is based on the vision-as-inverse-graphics paradigm and will use object models capturing coarse 3D shape and appearance, which can be learned from limited data, combined with hybrids of enumerative search-based inference and fast template-matching-based detectors. My goal is to present a few-shot scene understanding system and to study this system’s speed, accuracy, robustness, costs (data, compute) as compared to deep learning approaches.


I enjoyed my project on Bayesian inverse graphics from the past year, and I am confident that the collaborations and mentorship from my UROP supervisors and PIs have meaningfully impacted my MIT experience. By continuing my involvement with the project as a SuperUROP student, I hope to gain broader and deeper understanding of the research field, and to make a unique contribution at the intersection of computer vision and computational cognitive science.

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