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I successfully defended my thesis and will be starting as a postdoc at UC Berkeley with Jitendra Malik this Fall! You should be directed to my new website in 3 seconds. I am a PhD student at the Computer Science Department in the
University of Maryland, College Park, working with my advisor
David Jacobs. Since then I've had the pleasure to work with:
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Email: kanazawa at umiacs.umd.edu
Homepage: this page |
personal
Office: Room 4453 A.V. Williams Building
Mail: Department of Computer Science and UMIACS
A.V. Williams Building, University of Maryland
College Park, MD 20742
My work focuses on 3D reconstruction of animals including humans from single-view images. I work with animals because I am interested in how to represent non-rigid 3D shapes that deform and articulate. In particular I'm interested in how we can build a model of non-rigid 3D shapes from 2D images or videos. Also, animal pictures are a lot of fun to work with.
I believe the key to solving this problem is having a strong prior on object pose and shape, which can resolve many of the ambiguities. I am also interested in exploring how deep learning methods can be used for building such models.
Single-View 3D Reconstruction of Animals
Angjoo Kanazawa
Doctoral Thesis, University of Maryland, August 2017
[pdf]
3D Menagerie: Modeling the 3D shape and pose of animals
Silvia Zuffi, Angjoo Kanazawa, David Jacobs, Michael J. Black
Computer Vision and Pattern Recognition (CVPR) 2017. (Spotlight)
[pdf] [arXiv]
Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image
Federica Bogo*, Angjoo Kanazawa*, Christoph Lassner, Peter Gehler,
Javier Romero and Michael J. Black
(* equal contribution)
European Conference on Computer Vision (ECCV) 2016. (Spotlight)
[pdf] [project page with code] [Spotlight video ]
WarpNet: Weakly Supervised Matching for Single-View Reconstruction
Angjoo Kanazawa, David W. Jacobs, Manmohan Chandraker
Computer Vision and Pattern Recognition (CVPR) 2016.
[pdf]
[supp]
[test set ids & our curves]
Learning 3D Deformation of Animals from 2D Images
Angjoo Kanazawa, Shahar Kovalsky, Ronen Basri, David W. Jacobs
Eurographics 2016. Günter Enderle Best Paper Award
[pdf] [code
on github] [fastforward]
[cat results]
Locally Scale-invariant Convolutional Neural Network
Angjoo Kanazawa, Abhishek Sharma, David W. Jacobs
Deep Learning and Representation Learning Workshop: NIPS 2014.
[pdf][code on github]
Affordance of Object Parts from Geometric Features
Austin Myers, Angjoo Kanazawa, Cornelia Fermuller, Yiannis Aloimonos
RGB-D: Advanced Reasoning with Depth Cameras: RSS 2014 [pdf]
Vision Meets Cognition Workshop: CVPR 2014 [pdf]
Dog Breed Classification Using Part Localization
Jiongxin Liu, Angjoo Kanazawa, Peter Belhumeur, David W. Jacobs
European Conference on Computer Vision (ECCV), Oct. 2012.
[pdf] [slides]
try our iPhone app: Dogsnap !
Columbia dogs with parts dataset used in the paper: zip file (1.1GB)
133 breeds recognized by the American Kennel Club
8,351 images of dogs from Google image search, Image-net, and Flickr.
8 part locations annotated for each image
Teaching Assistant: CMSC 421 Spring 2012 Introduction to Artificial Intelligence
Teaching Assistant: CMSC 131 Fall 2011 Object-Oriented Programming I
Teaching Assistant: CSCI-UA.0101,0103, Fall 2008, Spring 2009 Introduction to Computer Science I, II