Charig Yang

I am a fourth (final) year PhD student at the Visual Geometry Group (VGG) at University of Oxford, advised by Andrew Zisserman and Weidi Xie. I am also interning at Meta from June to December 2024, and am expected to graduate by April 2025.

I am also part of Autonomous Intelligent Machines and Systems at University of Oxford, and am generously funded by EPSRC and AIMS.

I did my undergraduate in Engineering Science, also at Oxford. During which, I spent lovely summers at Japan Railways, Metaswitch, True, CP Group, and Oxford’s Engineering Department.

Prior to which, I was born and raised in the suburbs of Bangkok, Thailand.

Email  /  CV  /  Twitter  /  Github  /  Google Scholar

My PhD research explores novel methods in learning and using temporal signals in videos. I am particularly interested in: video understanding, self-supervised learning, segmentation, and new applications.

Shuffling and ordering sequences reveals changes that are monotonic over time

SAM + Optical Flow = FlowSAM

We show that neural networks can read analog clocks without manual supervision.

We use transformers to group independently moving parts into layers, resulting in self-supervised segmentation.

We consider the task of camouflaged animal discovery and present a large-scale video camouflage dataset.

2022-23: A2 (second-year) Electronic and Information Engineering, B14 (third-year) Information Engineering Systems, C18 (fourth-year) Computer Vision and Robotics
2021-22: B14 (third-year) Information Engineering Systems
2020-21: P2 (first-year) Electronic and Information Engineering, A1 (second-year) Mathematics, C19 (fourth-year) Machine Learning

You can find my summary notes for all P and A modules, and some B modules here.

Template gratefully stolen from here.