Angjoo Kanazawa

Angjoo Kanazawa 

I am an Assistant Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. I lead the Kanazawa AI Research (KAIR) lab under BAIR. I am also a Research Scientist at Google Research, and serve on the advisory board of Wonder Dynamics.

Previously, I was a BAIR postdoc at UC Berkeley advised by Jitendra Malik, Alexei A. Efros and Trevor Darrell. I completed my PhD in Computer Science at the University of Maryland, College Park with my advisor David Jacobs. During my PhD, I had the pleasure to visit the Max Planck Institute in Tübingen, Germany under the guidance of Michael Black. Prior to that, I spent four years at NYU where I worked with Rob Fergus and completed my BA in Mathematics and Computer Science.

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Email: kanazawa (at)

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My research lies at the intersection of computer vision, computer graphics, and machine learning. We live in a 3D world that is dynamic, full of life with people and animals interacting with the environment. How can we build a system that can capture, perceive, and understand these embodied agents in the 3D world from everyday photograph and video? The goal of my lab is to answer this question.

Kanazawa AI Research (KAIR) members

Distinguished Berkeley Computer Vision Fellow


Graduate Students





Infinite Nature: Perpetual View Generation of Natural Scenes from a Single Image
Andrew Liu*, Richard Tucker*, Varun Jampani, Ameesh Makadia, Noah Snavely, Angjoo Kanazawa
ICCV 2021 (Oral)
[Project Page with Demo] [Paper] [Code] [bibtex]

PlenOctrees for Real-time Rendering of Neural Radiance Fields
Alex Yu, Ruilong Li, Matthew Tancik, Hao Li, Ren Ng, Angjoo Kanazawa
ICCV 2021 (Oral)
[Project Page with Demo] [Paper] [Code] [bibtex]

Reconstructing Hand-Object Interactions in the Wild
Zhe Cao, Ilija Radosavovic, Angjoo Kanazawa, Jitendra Malik
ICCV 2021
[Project Page] [Paper] [Code coming soon] [bibtex]

AI Choreographer: Music Conditioned 3D Dance Generation with AIST++
Ruilong Li*, Shan Yang*, David A. Ross, Angjoo Kanazawa
ICCV 2021
[Project Page] [Paper] [Dataset] [Code] [bibtex]

AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control
Xue Bin Peng*, Ze Ma*, Pieter Abbeel, Sergey Levine, Angjoo Kanazawa
[Project Page] [Paper] [Code] [bibtex]

KeypointDeformer: Unsupervised 3D Keypoint Discovery for Shape Control
Tomas Jakab, Richard Tucker, Ameesh Makadia, Jiajun Wu, Noah Snavely, Angjoo Kanazawa
CVPR 2021 (Oral)
[Project website][Paper] [Code] [bibtex]

pixelNeRF: Neural Radiance Fields from One or Few Images
Alex Yu, Vickie Ye, Matthew Tancik, Angjoo Kanazawa
CVPR 2021
[Project Page/Code] [paper] [bibtex]

De-rendering the World's Revolutionary Artefacts
Shangzhe Wu, Ameesh Makadia, Jiajun Wu, Noah Snavely, Richard Tucker, Angjoo Kanazawa
CVPR 2021
[Project website] [Paper] [bibtex]

An Analysis of SVD for Deep Rotation Estimation
Jake Levinson, Carlos Esteves, Kefan Chen, Noah Snavely, Angjoo Kanazawa, Afshin Rostamizadeh, Ameesh Makadia
NeurIPS 2020
[Github] [paper] [bibtex]

Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild
Jason Y. Zhang*, Sam Pepose*, Hanbyul Joo, Deva Ramanan, Jitendra Malik, Angjoo Kanazawa
ECCV 2020
[project page] [Github] [arXiv preprint] [bibtex]

Shape and Viewpoint without Keypoints
Shubham Goel, Angjoo Kanazawa, Jitendra Malik
ECCV 2020
[project page] [Github] [arXiv preprint] [bibtex]

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]

  • Featured in two minute papers
  • 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] [bibtex]

    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.
    [pdf] [bibtex]

    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] [bibtex]

    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] [bibtex]

    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] [bibtex]

    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] [bibtex]

    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] [bibtex]

    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] [bibtex] [Part Affordance Dataset] [bibtex]

    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] [bibtex]
    try our iPhone app: Dogsnap !
    Columbia dogs with parts dataset used in the paper: zip file (2.43GB)

    • 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
    [pdf] [slides]