About

I am an Assistant Professor at the University of Michigan and a Research Scientist at Facebook AI Research (FAIR).

I'm broadly interested in computer vision and machine learning. My research involves visual reasoning, vision and language, image generation, and 3D reasoning using deep neural networks.

I received my PhD from Stanford University, advised by Fei-Fei Li.

Students

PhD Students

Karan Desai
Nilesh Kulkarni (Co-advised with David Fouhey)
Mohamed El Banani
Chris Rockwell (Co-advised with David Fouhey)
Ang Cao
Tiange Luo (Co-advised with Honglak Lee)

Teaching

University of Michigan

EECS 498/598: Deep Learning for Computer Vision [Fall 2019] [Fall 2020] [Winter 2022]
EECS 442: Computer Vision [Winter 2020] [Winter 2021]

Stanford University

CS 231N: Convolutional Neural Networks for Visual Recognition (2017 Lecture Videos)

Spring 2019, Spring 2018, Spring 2017 with Serena Yeung and Fei-Fei Li
Winter 2016 with Andrej Karpathy and Fei-Fei Li

Publications

Bootstrap Your Own Correspondences

Mohamed El Banani, Justin Johnson

ICCV 2021 (Oral)

[arXiv] [project] [code]

PixelSynth: Generating a 3D-Consistent Experience from a Single Image

Chris Rockwell, David Fouhey, Justin Johnson

ICCV 2021

[arXiv] [project] [code]

Rethinking "Batch" in BatchNorm

Yuxin Wu, Justin Johnson

arXiv 2021

[arXiv] [code]

UnsupervisedR&R: Unsupervised Point Cloud Registration via Differentiable Rendering

Mohamed El Banani, Luya Gao, Justin Johnson

CVPR 2021 (Oral)

[arXiv] [project] [code]

CASTing Your Model: Learning to Localize Improves Self-Supervised Representations

Ramprasaath R. Selvaraju*, Karan Desai*, Justin Johnson, Nikhil Naik

CVPR 2021

[arXiv] [blog]

VirTex: Learning Visual Representations from Textual Annotations

Karan Desai, Justin Johnson

CVPR 2021

[arXiv] [GitHub] [docs] [video]

Accelerating 3D Deep Learning with PyTorch3D

Nikhila Ravi, Jeremy Reizenstein, David Novotny, Taylor Gordon,
Wan-Yen Lo, Justin Johnson, Georgia Gkioxari

arXiv 2020

[arXiv] [website] [GitHub]

Temporal Reasoning via Audio Question Answering

Haytham Fayek, Justin Johnson

IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2020

[arXiv] [code]

SynSin: End-to-end View Synthesis from a Single Image

Olivia Wiles, Georgia Gkioxari, Richard Szeliski, Justin Johnson

CVPR 2020 (Oral)

[arXiv] [project] [code]

PHYRE: A New Benchmark for Physical Reasoning

Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, Ross Girshick

NeurIPS 2019

[arXiv] [project] [code]

Mesh R-CNN

Georgia Gkioxari, Jitendra Malik, Justin Johnson

ICCV 2019

[arXiv] [project]

On Network Design Spaces for Visual Recognition

Ilija Radosavovic, Justin Johnson, Saining Xie, Wan-Yen Lo, Piotr Dollár

ICCV 2019

[arXiv] [code]

HiDDeN: Hiding Data With Deep Networks

Jiren Zhu*, Russell Kaplan*, Justin Johnson, Li Fei-Fei
[* indicates equal contribution]

ECCV 2018

[arXiv] [code]

Image Generation from Scene Graphs

Justin Johnson, Agrim Gupta, Li Fei-Fei

CVPR 2018

[arXiv] [code]

Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks

Agrim Gupta, Justin Johnson, Li Fei-Fei, Silvio Savarese, Alexandre Alahi

CVPR 2018

[arXiv] [code]

Inferring and Executing Programs for Visual Reasoning

Justin Johnson, Bharath Hariharan, Laurens van der Maaten,
Judy Hoffman, Li Fei-Fei, C. Lawrence Zitnick, Ross Girshick

ICCV 2017 (Oral)

[project] [code] [arXiv] [video]

Characterizing and Improving Stability in Neural Style Transfer

Agrim Gupta, Justin Johnson, Alexandre Alahi, Li Fei-Fei

ICCV 2017

[arXiv]

CLEVR: A Diagnostic Dataset for
Compositional Language and Elementary Visual Reasoning

Justin Johnson, Bharath Hariharan, Laurens van der Maaten,
Li Fei-Fei, C. Lawrence Zitnick, Ross Girshick

CVPR 2017

[project] [code] [arXiv]

A Hierarchical Approach for Generating Descriptive Image Paragraphs

Jonathan Krause, Justin Johnson, Ranjay Krishna, Li Fei-Fei

CVPR 2017 (Spotlight)

[project] [arXiv] [dataset] [video]

Visual Genome: Connecting Language and Vision
using Crowdsourced Dense Image Annotations

Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson,
Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis,
Li-Jia Li, David A. Shamma, Michael Bernstein, Li Fei-Fei

IJCV 2017

[project] [pdf] [arXiv]

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

Justin Johnson, Alexandre Alahi, Li Fei-Fei

ECCV 2016

[project] [code] [pdf] [arXiv] [supplementary]

DenseCap: Fully Convolutional Localization Networks for Dense Captioning

Justin Johnson*, Andrej Karpathy*, Li Fei-Fei
[* indicates equal contribution]

CVPR 2016 (Oral)

[project] [code] [pdf] [arXiv] [data splits] [slides] [video]

Visualizing and Understanding Recurrent Networks

Andrej Karpathy*, Justin Johnson*, Li Fei-Fei
[* indicates equal contribution]

ICLR Workshop 2016

[pdf] [arXiv]

Love Thy Neighbors: Image Annotation by Exploiting Image Metadata

Justin Johnson*, Lamberto Ballan*, Li Fei-Fei
[* indicates equal contribution]

ICCV 2015

[pdf] [bib] [arXiv]

Image Retrieval using Scene Graphs

Justin Johnson, Ranjay Krishna, Michael Stark, Li-Jia Li, David A. Shamma,
Michael Bernstein, Li Fei-Fei

CVPR 2015

[pdf] [bib] [dataset (2GB)] [supplementary]

Side Projects

neural-style

A Torch implementation of the neural style transfer algorithm from the paper "A Neural Algorithm of Artistic Style" by Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge.

torch-rnn

Train character-level language models in torch, and sample from them to generate text. The language model is implemented with efficient, reusable RNN and LSTM modules.

simple-amt

A micro-framework that makes it easy to create and launch tasks on Amazon's Mechanical Turk.

cnn-benchmarks

Benchmarks for popular convolutional neural network models on different GPUs.