Richard Zhang

Research Scientist
Adobe Research
San Francisco, CA

rizhang at adobe.com
[GitHub] [Google Scholar]


I recently joined Adobe Research as a Research Scientist. I was previously a PhD student at UC Berkeley, advised by Professor Alexei (Alyosha) Efros. I obtained my BS and MEng degrees from Cornell University in ECE. My research interests are in computer vision, machine learning, deep learning, graphics, and image procesing.


Internship

If you have similar interests and are interested in collaborating during a summer 2019 internship, feel free to contact me. Please tell me about your past research experience and what you would potentially like to do. The goal of an internship is a publication, typically CVPR or SIGGRAPH (see my two most recent publications, which were from my summer 2017 internship). Interns are typically PhD students. The number of slots is limited, so we unfortunately cannot accept everyone.


News

[Aug 2018] I will be presenting at the Thesis Fast Forward session at SIGGRAPH on Tuesday 8/14, 2:00pm.
[Jun 2018] We will be presenting our project on perceptual metrics at CVPR, Tuesday 6/19, 10:10am. Try our metric here!
[May 2018] I have graduated from UC Berkeley and have joined Adobe Research as a Research Scientist in San Francisco!


Publications

The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, Oliver Wang
In CVPR, 2018.
[Paper] [Webpage] [GitHub] [Poster] [Adobe Blog] [Two Min Papers] [Bibtex]
Toward Multimodal Image-to-Image Translation
Jun-Yan Zhu, Richard Zhang, Deepak Pathak, Trevor Darrell, Alexei A. Efros, Oliver Wang, Eli Shechtman
In NIPS, 2017.
[Paper] [Webpage] [GitHub] [Video (YouTube)(mp4)] [Poster] [Two Min Papers] [Bibtex]
Real-Time User-Guided Image Colorization with Learned Deep Priors
Richard Zhang*, Jun-Yan Zhu*, Phillip Isola, Xinyang Geng, Angela S. Lin, Tianhe Yu, Alexei A. Efros
(*indicates equal contribution)
In SIGGRAPH, 2017.
[Paper] [Webpage] [Fastforward] [Talk] [Video (YouTube)(mp4)] [GitHub] [Slides (141mb)] [Bibtex]
Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction
Richard Zhang, Phillip Isola, Alexei A. Efros
In CVPR, 2017.
[Paper] [Webpage] [GitHub] [Poster] [Seminar Talk] [Bibtex]
Colorful Image Colorization
Richard Zhang, Phillip Isola, Alexei A. Efros
In ECCV, 2016 (oral presentation).
[Paper] [Webpage] [GitHub] [Talk] [Slides (138mb)] [Poster] [Bibtex]
Sensor Fusion for Semantic Segmentation of Urban Scenes
Richard Zhang, Stefan Candra, Kai Vetter, Avideh Zakhor
In ICRA, 2015.
[Paper (pdf)(official)] [Slides] [Poster] [Talk] [Annotations (tar)(zip) ] [Bibtex]
Automatic Identification of Window Regions on Indoor Point Clouds Using LiDAR and Cameras
Richard Zhang, Avideh Zakhor
In WACV, 2014.
[Paper (pdf)(official)] [Bibtex]

Thesis

Image Synthesis for Self-Supervised Visual Representation Learning
Richard Zhang
Spring 2018.
[Thesis] [Dissertation Talk] [Fast Forward] [Slides (396 MB)] [Bibtex]

Teaching

Introduction to Artificial Intelligence (CS 188), UC Berkeley
Graduate Student Instructor (GSI) with Prof. Anca Dragan
Spring 2017

Computer Vision (CS 280), UC Berkeley
Graduate Student Instructor (GSI) with Prof. Alexei A. Efros, Prof. Trevor Darrell
Spring 2016

Introduction to Circuits (ECE 2100), Cornell University
Teaching Assistant (TA) with Prof. Alyosha Molnar
Spring 2010

Awards

Thesis Fast Forward, Best Presentation, SIGGRAPH 2018
Adobe Research Fellowship 2017


Mentorship

I have had the opportunity to work with some talented students.

Undergraduate Researchers
Sheng-Yu Wang
Hemang Jeetendra Jangle
Xin Qin (now @ USC)
Angela S. Lin (now @ UT Austin)
Xinyang Geng (now @ UC Berkeley)
Tianhe Yu (now @ Stanford)
Stefan A. Candra