Deep down the rabbit hole: CVPR 2015 and beyond
CVPR is the premier Computer Vision conference, and it's fair to think of it as the Olympics of…
Showing posts with the label MIT
Mobileye's quest to put Deep Learning inside every new car
In Amnon Shashua's vision of the future, every car can see . He's convinced that the key t…
Understanding the Visual World, one 3D reconstruction at a time
The first generation of datasets in the computer vision community were just plain old images -- si…
Brand Spankin' New Vision Papers from ICCV 2013
The International Conference of Computer Vision, ICCV, gathers the world's best researchers in …
Can you pass the HOGgles test? Inverting and Visualizing Features for Object Detection
Despite more than a decade of incessant research by some of the world's top computer vision res…
Why your vision lab needs a reading group
I have a certain attitude when it comes to computer vision research -- don't do it in isolation…
Using Panoramas for Better Scene Understanding
There's a lot more to automated object interpretation than merely predicting the correct catego…
learning to "borrow" examples for object detection. Lim et al, NIPS 2011
Let's say you want to train a cat detector... If you're anything like me, then you probabl…
plenoptica theoretica: fields vs. particles
"All bodies together, and each by itself, give off to the surrounding air an infinite number o…