Jonathan Long

I am a PhD candidate at UC Berkeley, working on computer vision and advised by Trevor Darrell.

Before 2010, I was at Carnegie Mellon, studying Computer Science, Physics, and Mathematics.

I care about recognition: algorithms that learn to decode perceptual input into useful information.

I obsess about having the most powerful tools for research and engineering; I'm a developer of Caffe.

@longjon on GitHub

Fully Convolutional Networks for Semantic Segmentation

Jon Long*, Evan Shelhamer*, Trevor Darrell (CVPR 2015 best paper honorable mention)
*equal contribution

Fully convolutional networks by themselves, trained end-to-end on segmentation data, initialized from recent classification models, and with extra links between nonconsecutive layers, improve semantic segmentation on PASCAL by 20% relative.

Do Convnets Learn Correspondence?

Jon Long, Ning Zhang, Trevor Darrell (NIPS 2014)

Max-pooling convolutional networks trained on classification perform surprisingly well at fine-scale tasks like alignment and keypoint prediction.