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Richard Zhang - UC Berkeley

University of California at Berkeley. Richzhang at eecs.berkeley.edu. I am a PhD student in the EECS department at the University of California, Berkeley, advised by Professor Alexei (Alyosha) Efros. I obtained my Bachelor of Science and Master of Engineering degrees from Cornell University in Electrical and Computer Engineering (ECE). My research interests are in Computer Vision, Machine Learning, Deep Learning, and Sensor Fusion. Richard Zhang, Phillip Isola. Alexei A. Efros. Alexei A. Efros.

http://richzhang.github.io/

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Richard Zhang - UC Berkeley | richzhang.github.io Reviews
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University of California at Berkeley. Richzhang at eecs.berkeley.edu. I am a PhD student in the EECS department at the University of California, Berkeley, advised by Professor Alexei (Alyosha) Efros. I obtained my Bachelor of Science and Master of Engineering degrees from Cornell University in Electrical and Computer Engineering (ECE). My research interests are in Computer Vision, Machine Learning, Deep Learning, and Sensor Fusion. Richard Zhang, Phillip Isola. Alexei A. Efros. Alexei A. Efros.
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KEYWORDS
1 richard zhang
2 phd student
3 eecs department
4 github
5 google scholar
6 publications
7 arxiv
8 webpage
9 bibtex
10 colorful image colorization
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Richard Zhang - UC Berkeley | richzhang.github.io Reviews

https://richzhang.github.io

University of California at Berkeley. Richzhang at eecs.berkeley.edu. I am a PhD student in the EECS department at the University of California, Berkeley, advised by Professor Alexei (Alyosha) Efros. I obtained my Bachelor of Science and Master of Engineering degrees from Cornell University in Electrical and Computer Engineering (ECE). My research interests are in Computer Vision, Machine Learning, Deep Learning, and Sensor Fusion. Richard Zhang, Phillip Isola. Alexei A. Efros. Alexei A. Efros.

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richzhang.github.io richzhang.github.io
1

Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction

http://richzhang.github.io/splitbrainauto

Unsupervised Learning by Cross-Channel Prediction. Alexei A. Efros. To perform unsupervised pretraining, we split a network in half in the channel direction to produce two disjoint subnetworks. Each subnetwork is then trained to perform prediction on one subset of data from another subset. (Left) Images. Half of the network predicts color channels from grayscale, and the other half predicts grayscale from color. (Right) RGB-D Images. From other channels of raw data. We also show performance on several co...

2

Colorful Image Colorization

http://richzhang.github.io/colorization

Alexei A. Efros. Example input grayscale photos and output colorizations from our algorithm. These examples are cases where our model works especially well. For randomly selected examples, see the Performance comparisons. How to interpret the results. And the figure here. This is partly because our algorithm is trained on one million images from the Imagenet dataset, and will thus work well for these types of images, but not necessarily for others. We call this the "dataset bias". Try the Interactive Demo.

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www-video.eecs.berkeley.edu www-video.eecs.berkeley.edu

VIP Lab - People

http://www-video.eecs.berkeley.edu/people.shtml

Skip to main content. Electrical Engineering and Computer Sciences. Staff and Visiting Scientists. 3D Image Processing and Computer Vision. Image Processing for IC Lithography. Multimedia Search and Retrieval. Multimedia Networking and Commmunications. Image and Video Compression. Satarupa Mukherjee [PostDoc 2015]. Shicong Yang [MS 2014]. Michael Krishnan [PhD 2014]. Omar Oreifej [PostDoc 2014]. Peter Cheng [MS 2013]. Joe Carrow [Staff 2013]. Dr Wei Zhang [PostDoc 2011]. Dr Victor Sanchez [PostDoc 2011].

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