Info

I am interested in machine learning and it's application to computer vision. My work focuses mainly on image representations, broadly defined as problems where the goal is to produce an image (or image-like object) as output. The difficulty of this style of problem in current practice lies in the inherently generative nature of the problem and the inherently discriminative nature of deep learning based machine learning.

I recently defended my dissertation, Learning and Evaluating Image Representations at the University of Illinois at Urbana Champaign for work done with David Forsyth. Prior to Illinois I received my BS from Rensselaer Polytechnic Institute where I worked with Chuck Stewart (RPI) and Scott Gallager (WHOI).

Research

Detecting Anomalous Faces with No Peeking Autoencoders.
Anand Bhattad, Jason Rock, David Forsyth
Arxiv, 2018

Authoring Image Decompositions with Generative Models
Jason Rock, Theerasit Issaranon, Aditya Deshpande, David Forsyth
ArXiv, 2016

Learning Large-Scale Automatic Image Colorization
Aditya Deshpande, Jason Rock, David Forsyth
International Conference on Computer Vision (ICCV), 2015

Completing 3D Object Shape from One Depth Image
Jason Rock, Tanmay Gupta, Justin Thorsen, JunYoung Gwak, Daeyun Shin, Derek Hoiem
Proc. IEEE Conf. on Computer Vision and Pattern Recognition ( CVPR ), 2015

Non-Parametric Filtering for Geometric Detail Extraction and Material Representations
Zicheng Liao, Jason Rock, Yang Wang, David Forsyth
Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2013

Boundary Cues for 3D Object Shape Recovery
Kevin Karsch, Zicheng Liao, Jason Rock, Jonathan Barron, Derek Hoiem
Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2013