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Computer Vision — Week 7

1 min read

Table of contents

Hey! My name’s Michel Liao. I’m a computer science first-year at Princeton University, hoping to get a PhD in computer vision. Join me in my CV journey!



I watched this image stitching series by Professor Shree Nayar. Notes here!

I’m working on this optical flow series by Prof. Nayar.

Mini Projects

I worked on a homography assignment created by Erich Liang. You can find the code here, but I won’t be implementing the rest of the assignment unless I have free time.

Course Progress

Finished Coursera’s Unsupervised Learning course, completing their ML series! Find my notes on unsupervised learning here.

Now, I’m on their deep learning series.

Paper of the Week

No paper this week.


Most of the insights for this week are in the notes I’ve linked above!

  • Homogeneous coordinates allow us to represent translations in terms of a 3x3 transformation matrix.
  • Reinforcement learning doesn’t teach the model exactly how it should act. Rather, it just defines certain goals that are good (rewards) and the NN will figure out how it should act.

Going Forward

I’m going to shift my focus to Prof. Nayar’s optical flow lectures and read a paper on RAFT. I’ll work on the deep learning series, too.

Michel Liao

Michel Liao

Boise, Idaho, United States
Hello! I'm a sophomore studying computer science at Princeton. I like reading, rock climbing, and running.