YOLOv3

YOLOv3 is out. See paper here and code here. The YOLO paper series is always fun to read. 🙂 Some highlights are

  • It is worse than RetinaNet but is 3.8 times faster
  • Comparable as SSD but 3 times faster
  • One thing interesting thing mentioned in the paper is that focal cost doesn’t seem to help

The Network Effect

This is some notes from an Q&A of Yann Lecun appeared in the March 2018 issue of Communications of ACM.

What are some of the things going on at FAIR that most interest or excite you?

  • … One is marrying reasoning with learning. A lot of learning has to do with perceptions, which are relatively simple things that people can do without thinking too much. But we haven’t yet found good recipes for training systems to do tasks that require a little bit of reasoning. There is some work in that direction, but it’s not where we want it.
  • unsupervised learning—teaching machines to learn by observing the world, say by watching videos or looking at images without being told what objects are in these images
  • autonomous AI systems whose behavior is not directly controlled by a person. In other words, they are designed not just to do one particular task, but to make decisions and adapt to different circumstances on their own.
Copyright OU-Tulsa Lab of Image and Information Processing 2019
Tech Nerd theme designed by Siteturner