Angjoo Kanazawa

Angjoo Kanazawa 

I will be starting as an Assistant Professor at UC Berkeley from Fall 2020.

I am a research scientist at Google NYC. Previously, I was a BAIR postdoc at UC Berkeley advised by Jitendra Malik, Alexei A. Efros and Trevor Darrell.
I completed my PhD in CS at the University of Maryland, College Park with my advisor David Jacobs. Prior to UMD, I spent four years at NYU where I worked with Rob Fergus and completed my BA in Mathematics and Computer Science.

Since then I've had the pleasure to work with:


Prospective students: I am looking for students to start with me in Fall 2020. Click here for details.


Email: kanazawa at
Homepage: this page


Three-D Safari: Learning to Estimate Zebra Pose, Shape, and Texture from Images "In the Wild"
Silvia Zuffi, Angjoo Kanazawa, Tanya Berger-Wolf, Michael J. Black
ICCV 2019
[Github] [arXiv preprint] [bibtex]

PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization
Shunsuke Saito*, Zeng Huang*, Ryota Natsume*, Shigeo Morishima, Angjoo Kanazawa, Hao Li
(* equal contribution)
ICCV 2019
[project page] [arXiv preprint] [video] [bibtex]

Predicting 3D Human Dynamics from Video
Jason Y. Zhang, Panna Felsen, Angjoo Kanazawa, Jitendra Malik
ICCV 2019
[project page] [arXiv preprint] [video] [bibtex]

Learning 3D Human Dynamics from Video
Angjoo Kanazawa*, Jason Y. Zhang*, Panna Felsen*, Jitendra Malik
CVPR 2019
[project page] [arXiv preprint] [video] [bibtex]

Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow
Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, Sergey Levine
ICLR 2019
[project page] [code] [arXiv preprint] [video] [bibtex]

SFV: Reinforcement Learning of Physical Skills from Videos
Xue Bin Peng, Angjoo Kanazawa, Jitendra Malik, Pieter Abbeel, Sergey Levine
ACM Transactions on Graphics (Proc. SIGGRAPH Asia 2018)
[project page] [pdf] [BAIR Blog] [arXiv preprint] [video] [bibtex]

Learning Category-Specific Mesh Reconstruction from Image Collections
Angjoo Kanazawa*, Shubham Tulsiani*, Alexei A. Efros, Jitendra Malik
(* equal contribution)
ECCV 2018
[project page] [pdf] [arXiv preprint] [video] [bibtex]

End-to-end Recovery of Human Shape and Pose
Angjoo Kanazawa, Michael J. Black, David W. Jacobs, Jitendra Malik
CVPR 2018
[project page with code] [pdf] [arXiv preprint] [bibtex]

SfSNet : Learning Shape, Reflectance and Illuminance of Faces ‘in the wild’
Soumyadip Sengupta, Angjoo Kanazawa, Carlos D. Castillo, David W. Jacobs
CVPR 2018 (Spotlight)
[project page with code] [pdf] [arXiv preprint] [bibtex]

Lions and Tigers and Bears: Capturing Non-Rigid, 3D, Articulated Shape from Images
Silvia Zuffi, Angjoo Kanazawa, Michael J. Black
CVPR 2018 (Spotlight)
[project page with 3D models] [pdf]

Towards Accurate Marker-less Human Shape and Pose Estimation over Time
Yinghao Huang, Federica Bogo, Christoph Lassner, Angjoo Kanazawa, Peter V. Gehler, Javier Romero, Ijaz Akhter, Michael J. Black
International Conference on 3D Vision (3DV), 2017.

3D Menagerie: Modeling the 3D shape and pose of animals
Silvia Zuffi, Angjoo Kanazawa, David W. Jacobs, Michael J. Black
Computer Vision and Pattern Recognition (CVPR) 2017. (Spotlight)
[project page with model and demo] [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] [See the results here]

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] [Part Affordance Dataset]

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


Single-View 3D Reconstruction of Animals
Angjoo Kanazawa
Doctoral Thesis, University of Maryland, August 2017