Siyuan (Reed) Yang   杨思源

I am a PhD student at the Robotics Institute, part of the School of Computer Science at Carnegie Mellon University, where I work on 3D computer vision. My PhD advisor is Martial Hebert.

From 2011 to 2017, I worked at Intel, as part of Intel RealSense. I primarily designed computer vision algorithms for efficient hardware ASICs, including the Intel RealSense R200 and D400 RGB-D sensors. Additionally, I worked on software APIs, active illumination systems, human-computer interaction devices, and helped develop demos for trade shows, including CES 2012-2016.

I have an MS in Computer Science (AI focus) from Stanford University, where I was a research assistant for Silvio Savarese and a teaching assistant for Fei-Fei Li (CS131 & CS231N). I have a BS in EECS from UC Berkeley, where I worked in Kris Pister's lab.

Email  /  GitHub  /  CV

Research

I'm interested in computer vision, machine learning, optimization, graphics and robotics.

PDF: A Probability-Driven Framework for Open World 3D Point Cloud Semantic Segmentation

We propose a Probability-Driven Framework (PDF) for open world semantic segmentation that includes (i) a lightweight U-decoder branch to identify unknown classes by estimating uncertainties, (ii) a pseudo-labeling scheme to generate ground truth for unknown classes, and (iii) an incremental knowledge distillation strategy to incorporate novel classes.

Activities

My activities include conference and talkings.

Other Projects

These include coursework, side projects and unpublished research work.

Design and source code from Jon Barron's website