Jun-Yan Zhu

Ph.D. Student

Department of EECS

University of California, Berkeley

Email:

junyanz at eecs dot berkeley dot edu

Office:

Soda Hall 547
University of California, Berkeley
Berkeley, CA 94704

 

[CV] [Google Scholar]

 

I am a Computer Science Ph.D. student at UC Berkeley. Before coming here, I was a Ph.D. student in Computer Science Department at CMU. I am now working on computer graphics and computer vision with Professor Alexei A. Efros. My current research focuses on summarizing, mining and exploring large-scale visual data collections, with the goal of building a digital bridge between Humans and Big Visual Data. I am currently supported by a Facebook Fellowship

 

I received my B.E in Computer Science from Tsinghua University in 2012, where I worked with Professor Zhuowen Tu and Dr. Eric Chang at Microsoft Research Asia. I was also a member of Tsinghua's Graphics Group led by Professor Shi-Min Hu.

 

I adopted Aquarius, a sweet and serene cat. Check out her personal photos. I am also maintaining Cat Paper Collection for our cat lovers in academics.

 

 

 

Recent Talks

-- Mirror Mirror: Crowdsourcing Better Portraits

ACM SIGGRAPH Asia 2014 (Dec 2014)

-- What Makes Big Visual Data Hard?

ACM SIGGRAPH Asia 2014 invited course "Data-Driven Visual Computing" (Dec 2014)

-- AverageExplorer: Interactive Exploration and Alignment of Visual Data Collections

ACM SIGGRAPH 2014 (Aug 2014)

-- Discovering Objects and Harvesting Visual Concepts via Weakly Supervised Learning

Berkeley Visual Computing Lab Noon Talk (Mar 2014)

 

 

 

Publications

 

Learning a Discriminative Model for the Perception of Realism in Composite Images

Jun-Yan Zhu, Philipp Krähenbühl , Eli Shechtman and Alexei A. Efros

In IEEE International Conference on Computer Vision(ICCV 2015)

 

[Project Page (with Code and Data)] [Paper]

[Slides] [Poster] [BibTex]

 

Mirror Mirror: Crowdsourcing Better Portraits

Jun-Yan Zhu, Aseem Agarwala, Alexei A. Efros, Eli Shechtman and Jue Wang

In ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2014)

 

[Project Page (with Code) ] [Paper] [Data]

[Slides] [Supplement] [BibTex]

AverageExplorer: Interactive Exploration and Alignment of Visual Data Collections

Jun-Yan Zhu, Yong Jae Lee and Alexei A. Efros

In ACM Transactions on Graphics (Proceedings of SIGGRAPH 2014)

 

See article in The New Yorker

[Project Page] [YouTube] [Paper]

[Slides] [Supplement] [BibTex]

 

Unsupervised Object Class Discovery via Saliency-Guided Multiple Class Learning

Jun-Yan Zhu, Jiajun Wu, Yan Xu, Eric Chang and Zhuowen Tu

In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014

(an expanded journal version of our CVPR 2012 paper)

 

[Project Page] [Paper]

[Supplement] [Poster] [BibTex]

 

Weakly Supervised Histopathology Cancer Image Segmentation and Classification

Yan Xu, Jun-Yan Zhu, Eric I-Chao Chang, Maode Lai and Zhuowen Tu

In Medical Image Analysis (MIA), 2014

(an expanded journal version of our CVPR 2012 paper)

 

[Project Page] [Code] [Paper] [BibTex]

 

MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation

Jiajun Wu*, Yibiao Zhao*, Jun-Yan Zhu, Siwei Luo and Zhuowen Tu

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014

 

[Project Page] [Paper] [Poster] [BibTex]

Reverse Image Segmentation: A High-Level Solution to a Low-Level Task

Jiajun Wu, Jun-Yan Zhu and Zhuowen Tu

In British Machine Vision Conference (BMVC), 2014

 

[Paper] [BibTex]

 

Motion-Aware Gradient Domain Video Composition

Tao Chen, Jun-Yan Zhu, Ariel Shamir and Shi-Min Hu

In IEEE Transactions on Image Processing (TIP), 2013

 

[Paper] [Youtube] [Video] [BibTex]

 

Multiple Clustered Instance Learning for Histopathology Cancer Image Segmentation, Clustering, and Classification

Yan Xu*, Jun-Yan Zhu*, Eric Chang and Zhuowen Tu (*equal contribution)

In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012

 

[Project Page] [Code] [Paper] [Poster] [BibTex]

 

 

 

Software

 

RealismCNN: code for predicting and improving visual realism in composite images

MCILBoost: a boosting-based Multiple Instance Learning (MIL) package that includes MIL-Boost and MCIL-Boost

MirrorMirror: an expression training App that helps users mimic their own expressions

SelectGoodFace: a program for selecting attractive/serious portraits from a personal photo collection

FaceDemo: a simple 3D face alignment and warping demo

 

 

 

Awards

 

Facebook Fellowship (2015-2017)

Outstanding Undergraduate Thesis in Tsinghua University (2012)

Excellent Undergraduate Student in Tsinghua University (2012)

National Scholarship, by Ministry of Education of China (2009 and 2010)

Singapore Technologies Engineering China Scholarship (2010, 2011, and 2012)

 

 

 

Patents

 

US 20140270495. Multiple Cluster Instance Learning for Image Classification

US 20140140610. Unsupervised Object Class Discovery via Bottom Up Multiple Class Learning

 

 

 


Since August 2014