Richard Zhang

 Senior Research Scientist
Adobe Research
San Francisco, CA

rizhang at adobe.com
[GitHub] [Google Scholar]
[Resume/CV] [Twitter] [Bio]

My research interests are in computer vision, machine learning, deep learning, graphics, and image processing. I obtained a PhD at UC Berkeley, advised by Prof. Alexei (Alyosha) Efros. I obtained BS and MEng degrees from Cornell University in ECE. I often collaborate with academic researchers, either through internships or university collaboration.

Recent media. I was included on MIT Technology Review's list of Innovators Under 35. Please see this Adobe blog post, overview video (5 min), or TWiML podcast below (40 min) for more on our work on perception, generation, and forensics for "GenAI".

News

[Sept 2024] Attribution by Unlearning and DMDv2 were accepted to NeurIPS 2024.
[Aug 2024] Check out TurboEdit, accepted to ECCV 2024.
[Jul 2024] Diffusion2GAN, Lazy Diffusion, and Editable Image Elements were accepted to ECCV 2024.
[Apr 2024] I'll be speaking at GenAI Media Challenge and Fair, Data-Efficient, and Trusted Computer Vision workshops.
[Feb 2024] DMD was accepted to CVPR 2024.
[Sept 2023] DreamSim was accepted to NeurIPS 2023 as a spotlight.

Publications

  Data Attribution for Text-to-Image Models by Unlearning Synthesized Images
Sheng-Yu Wang, Aaron Hertzmann, Alexei A. Efros, Jun-Yan Zhu, Richard Zhang
To appear in NeurIPS, 2024.
[Paper] [Webpage]
  Improved Distribution Matching Distillation for Fast Image Synthesis
Tianwei Yin, Michael Gharbi, Taesung Park Richard Zhang, Eli Shechtman, Fredo Durand, William T. Freeman
To appear in NeurIPS (oral), 2024.
[Paper] [Webpage] [Bibtex]
  Customizing Text-to-Image Diffusion with Camera Viewpoint Control
Nupur Kumari, Grace Su, Richard Zhang, Taesung Park, Jun-Yan Zhu
To appear in SIGGRAPH Asia, 2024.
[Paper] [Webpage] [GitHub] [Demo]
Customizing Motion in Text-to-Video Diffusion Models
Joanna Materzynska, Josef Sivic, Eli Shechtman, Antonio Torralba, Richard Zhang, Bryan Russell
To appear in ACCV, 2024.
[Paper] [Webpage] [Bibtex]
TurboEdit: Instant text-based image editing
Zongze Wu, Nicholas Kolkin, Jonathan Brandt, Richard Zhang, Eli Shechtman,
To appear in ECCV, 2024.
[Paper] [Webpage]
  Diffusion2GAN: Distilling Diffusion Models into Conditional GANs
Minguk Kang, Richard Zhang, Connelly Barnes, Sylvain Paris, Suha Kwak, Jaesik Park, Eli Shechtman, Jun-Yan Zhu, Taesung Park
To appear in ECCV, 2024.
[Paper] [Webpage] [Bibtex]
Editable Image Elements for Controllable Synthesis
Jiteng Mu, Michael Gharbi, Richard Zhang, Eli Shechtman, Nuno Vasconcelos, Xiaolong Wang, Taesung Park,
To appear in ECCV, 2024.
[Paper] [Webpage]
  Lazy Diffusion Transformer for Interactive Image Editing
Yotam Nitzan, Zongze Wu, Richard Zhang, Eli Shechtman, Daniel Cohen-Or, Taesung Park, Michael Gharbi
To appear in ECCV, 2024.
[Paper] [Webpage]
  One-step Diffusion with Distribution Matching Distillation
Tianwei Yin, Michael Gharbi, Richard Zhang, Eli Shechtman, Fredo Durand, William T. Freeman, Taesung Park
In CVPR, 2024.
[Paper] [Webpage] [Teaser] [Bibtex]
  Personalized Residuals for Concept-Driven Text-to-Image Generation
Cusuh Ham, Matthew Fisher, James Hays, Nick Kolkin, Yuchen Liu, Richard Zhang, Tobias Hinz,
In CVPR, 2024.
[Paper] [Webpage] [Bibtex]
  Image Neural Field Diffusion Models
Yinbo Chen, Oliver Wang, Richard Zhang, Eli Shechtman, Xiaolong Wang, Michael Gharbi
In CVPR, 2024 (highlight).
[Paper] [Webpage]
  VideoGigaGAN: Towards Detail-rich Video Super-Resolution
Yiran Xu, Taesung Park, Richard Zhang, Yang Zhou, Eli Shechtman, Feng Liu, Jia-Bin Huang, Difan Liu
In ArXiv, 2024.
[Paper] [Webpage] [Bibtex]
  Jump Cut Smoothing for Talking Heads
Xiaojuan Wang, Taesung Park, Yang Zhou, Eli Shechtman, Richard Zhang
In ArXiv, 2024.
[Paper] [Webpage]
  DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data
Stephanie Fu*, Netanel Tamir*, Shobhita Sundaram*, Lucy Chai, Richard Zhang, Tali Dekel, Phillip Isola
(*equal contribution)
To appear in NeurIPS (spotlight), 2023.
[Paper] [Webpage] [GitHub] [Bibtex]
  Evaluating Data Attribution for Text-to-Image Models
Sheng-Yu Wang, Alexei A. Efros, Jun-Yan Zhu, Richard Zhang
In ICCV, 2023.
[Paper] [Webpage] [GitHub] [Bibtex]
  Ablating Concepts in Text-to-Image Diffusion Models
Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman, Richard Zhang, Jun-Yan Zhu
In ICCV, 2023.
[Paper] [Webpage] [GitHub] [Bibtex]
  Online Detection of AI-Generated Images
David C. Epstein, Ishan Jain, Oliver Wang, Richard Zhang
In ICCV DFAD Workshop, 2023.
[Paper] [Webpage] [Slides] [Poster] [Bibtex]
  Zero-shot Image-to-Image Translation
Gaurav Parmar, Krishna Kumar Singh, Richard Zhang, Yijun Li, Jingwan Lu, Jun-Yan Zhu
In SIGGRAPH, 2023.
[Paper] [Webpage] [GitHub] [Demo]
    Scaling up GANs for Text-to-Image Synthesis
Minguk Kang, Jun-Yan Zhu, Richard Zhang, Jaesik Park, Eli Shechtman, Sylvain Paris, Taesung Park
In CVPR (highlight), 2023.
[Paper] [Webpage] [Bibtex]
  Multi-Concept Customization of Text-to-Image Diffusion
Nupur Kumari, Bingliang Zhang, Richard Zhang, Eli Shechtman, Jun-Yan Zhu
In CVPR, 2023.
[Paper] [Webpage] [GitHub] [Bibtex]
Domain Expansion of Image Generators
Yotam Nitzan, Michaël Gharbi, Richard Zhang, Taesung Park, Jun-Yan Zhu, Daniel Cohen-Or, Eli Shechtman
In CVPR, 2023.
[Paper] [Webpage] [GitHub] [Bibtex]
  The Low-Rank Simplicity Bias in Deep Networks
Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola
In TMLR, 2023.
[Paper] [Webpage] [GitHub] [Bibtex]
  Any-resolution Training for High-resolution Image Synthesis
Lucy Chai, Michaël Gharbi, Eli Shechtman, Phillip Isola, Richard Zhang
In ECCV, 2022.
[Paper] [Webpage] [GitHub] [Video] [Bibtex]
BlobGAN: Spatially Disentangled Scene Representations
Dave Epstein, Taesung Park, Richard Zhang, Eli Shechtman, Alexei A. Efros
In ECCV, 2022.
[Paper] [Webpage] [GitHub] [Video] [Bibtex]
  3D-FM GAN: Towards 3D-Controllable Face Manipulation
Yuchen Liu, Zhixin Shu, Yijun Li, Zhe Lin, Richard Zhang, Sun-Yuan Kung
In ECCV, 2022.
[Paper] [Webpage] [Video]
  ASSET: Autoregressive Semantic Scene Editing with Transformers at High Resolutions
Difan Liu, Sandesh Shetty, Tobias Hinz, Matthew Fisher, Richard Zhang, Taesung Park, Evangelos Kalogerakis
In SIGGRAPH, 2022.
[Paper] [Webpage] [GitHub] [Bibtex]
  GAN-Supervised Dense Visual Alignment
William Peebles, Jun-Yan Zhu, Richard Zhang, Alexei A. Efros, Antonio Torralba, Eli Shechtman
In CVPR (oral, best paper finalist), 2022.
[Paper] [Webpage] [GitHub] [Video] [Bibtex]
  Ensembling Off-the-shelf Models for GAN Training
Nupur Kumari, Richard Zhang, Eli Shechtman, Jun-Yan Zhu
In CVPR (oral), 2022.
[Paper] [Webpage] [GitHub] [Video] [Bibtex]
  Spatially-Adaptive Multilayer Selection for GAN Inversion and Editing
Gaurav Parmar, Yijun Li, Jingwan Lu, Richard Zhang, Jun-Yan Zhu, Krishna Kumar Singh
In CVPR, 2022.
[Paper] [Webpage] [GitHub] [Bibtex]
  On Aliased Resizing Libraries and Surprising Subtleties in FID Calculation
Gaurav Parmar, Richard Zhang, Jun-Yan Zhu
In CVPR, 2022.
[Paper] [Webpage] [GitHub] [Bibtex]
  Editing Conditional Radiance Fields
Steven Liu, Xiuming Zhang, Zhoutong Zhang, Richard Zhang, Jun-Yan Zhu, Bryan Russell
In ICCV, 2021.
[Paper] [Webpage] [GitHub] [Video] [Demo] [Bibtex]
  Contrastive Feature Loss for Image Prediction
Alex Andonian, Taesung Park, Bryan Russell, Phillip Isola, Jun-Yan Zhu, Richard Zhang.
In ICCV AIM Workshop, 2021.
[Paper] [GitHub] [Bibtex]
  Ensembling with Deep Generative Views
Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhang
In CVPR, 2021.
[Paper] [Webpage] [GitHub] [Video] [Colab] [Bibtex]
  Few-shot Image Generation via Cross-domain Correspondence
Utkarsh Ojha, Yijun Li, Jingwan Lu, Alexei A. Efros, Yong Jae Lee, Eli Shechtman, Richard Zhang
In CVPR, 2021.
[Paper] [Webpage] [GitHub] [Video] [Bibtex]
  Anycost GANs for Interactive Image Synthesis and Editing
Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zhu
In CVPR, 2021.
[Paper] [Webpage] [Video] [GitHub] [Bibtex]
  Spatially-Adaptive Pixelwise Networks for Fast Image Translation
Tamar Rott Shaham, Michaël Gharbi, Richard Zhang, Eli Shechtman, Tomer Michaeli
In CVPR, 2021.
[Paper] [Webpage] [Bibtex]
CDPAM: Contrastive Learning for Perceptual Audio Similarity
Pranay Manocha, Zeyu Jin, Richard Zhang, Adam Finkelstein
In ICASSP, 2021.
[Paper] [Webpage] [GitHub] [Bibtex]
    Swapping Autoencoder for Deep Image Manipulation
Taesung Park, Jun-Yan Zhu, Oliver Wang, Jingwan Lu, Eli Shechtman, Alexei A. Efros, Richard Zhang
In NeurIPS, 2020.
[Paper] [Webpage] [GitHub] [Video] [Bibtex]
  Few-shot Image Generation with Elastic Weight Consolidation
Yijun Li, Richard Zhang, Jingwan Lu, Eli Shechtman
In NeurIPS, 2020.
[Paper] [Supplemental] [Webpage] [Bibtex]
  Contrastive Learning for Unpaired Image-to-Image Translation
Taesung Park, Alexei A. Efros, Richard Zhang, Jun-Yan Zhu
In ECCV, 2020.
[Paper] [Webpage] [GitHub] [Teaser] [Video] [Bibtex]
Transforming and Projecting Images into Class-conditional Generative Networks
Minyoung Huh, Richard Zhang, Jun-Yan Zhu, Sylvain Paris, Aaron Hertzmann
In ECCV (oral), 2020.
[Paper] [Webpage] [GitHub] [Bibtex]
A Differentiable Perceptual Audio Metric Learned from Just Noticeable Differences
Pranay Manocha, Adam Finkelstein, Richard Zhang, Nicholas J. Bryan, Gautham J. Mysore, Zeyu Jin
In Interspeech, 2020.
[Paper] [Webpage] [GitHub] [Bibtex]
CNN-generated images are surprisingly easy to spot...for now
Sheng-Yu Wang, Oliver Wang, Richard Zhang, Andrew Owens, Alexei A. Efros
In CVPR, 2020 (oral).
[Paper] [Webpage] [GitHub] [Talk] [Bibtex]
Deep Parametric Shape Predictions using Distance Fields
Dmitriy Smirnov, Matthew Fisher, Vladimir G. Kim, Richard Zhang, Justin Solomon
In CVPR, 2020.
[Paper] [Webpage] [GitHub] [Video] [Bibtex]
Image Morphing with Perceptual Constraints and STN Alignment
Noa Fish, Richard Zhang, Lilach Perry, Daniel Cohen-Or, Eli Shechtman, Connelly Barnes
In CGF, 2020.
[Paper] [GitHub] [Bibtex]
Making Convolutional Networks Shift-Invariant Again
Richard Zhang
In ICML, 2019.
[Paper] [Webpage] [GitHub] [Talk] [Slides (129mb)] [Poster] [Bibtex]
Detecting Photoshopped Faces by Scripting Photoshop
Sheng-Yu Wang, Oliver Wang, Andrew Owens, Richard Zhang, Alexei A. Efros
In ICCV, 2019.
[Paper] [Webpage] [GitHub] [Video] [Poster] [Adobe Max] [Adobe Blog] [Bibtex]
Interactive Sketch & Fill: Multiclass Sketch-to-Image Translation
Arnab Ghosh, Richard Zhang, Puneet Dokania, Oliver Wang, Alexei A. Efros, Philip H.S. Torr, Eli Shechtman In ICCV, 2019.
[Paper] [Webpage] [GitHub] [Video] [Bibtex]
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, Oliver Wang
In CVPR, 2018.
[Paper] [Webpage] [GitHub] [Poster] [Adobe Blog] [Two Min Papers] [Bibtex]
Stochastic Adversarial Video Prediction
Alex X. Lee, Richard Zhang, Frederik Ebert, Pieter Abbeel, Chelsea Finn, Sergey Levine
In ArXiv, 2018.
[Paper] [Webpage] [GitHub] [Bibtex]
Toward Multimodal Image-to-Image Translation
Jun-Yan Zhu, Richard Zhang, Deepak Pathak, Trevor Darrell, Alexei A. Efros, Oliver Wang, Eli Shechtman
In NIPS, 2017.
[Paper] [Webpage] [GitHub] [Video (YouTube)(mp4)] [Poster] [Two Min Papers] [Bibtex]
Real-Time User-Guided Image Colorization with Learned Deep Priors
Richard Zhang*, Jun-Yan Zhu*, Phillip Isola, Xinyang Geng, Angela S. Lin, Tianhe Yu, Alexei A. Efros
(*equal contribution)
In SIGGRAPH, 2017.
[Paper] [Webpage] [Fastforward] [Talk] [Video (YouTube)(mp4)] [PSE 2020] [GitHub] [Slides (141mb)] [Bibtex]
Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction
Richard Zhang, Phillip Isola, Alexei A. Efros
In CVPR, 2017.
[Paper] [Webpage] [GitHub] [Poster] [Seminar Talk] [Bibtex]
Colorful Image Colorization
Richard Zhang, Phillip Isola, Alexei A. Efros
In ECCV, 2016 (oral).
[Paper] [Webpage] [GitHub] [Talk] [Slides (138mb)] [Poster] [Bibtex]
Sensor Fusion for Semantic Segmentation of Urban Scenes
Richard Zhang, Stefan Candra, Kai Vetter, Avideh Zakhor
In ICRA, 2015.
[Paper (pdf)(official)] [Slides] [Poster] [Talk] [Annotations (tar)(zip) ] [Bibtex]
Automatic Identification of Window Regions on Indoor Point Clouds Using LiDAR and Cameras
Richard Zhang, Avideh Zakhor
In WACV, 2014.
[Paper (pdf)(official)] [Bibtex]

Thesis

Image Synthesis for Self-Supervised Visual Representation Learning
Richard Zhang
Spring 2018.
[Thesis] [Dissertation Talk] [Fast Forward] [Slides (396 MB)] [Bibtex]

Organization, Committees

Sketching for Human Expressivity (SHE) at ECCV 2022 (co-organizer)
Advances in Image Manipulation (AIM) at ICCV 2019 (co-organizer)
CVPR 2020, 2021, 2023 (Area Chair)
BMVC 2022 (Area Chair)

Awards

MIT Technology Review, 35 Innovators Under 35, 2023
Reviewer recognitions, CVPR 2019, NeurIPS 2019, ECCV 2020, NeurIPS 2020, ECCV 2022
Thesis Fast Forward, Best Presentation, SIGGRAPH 2018
Adobe Research Fellowship 2017

Student collaborators/interns

I have gotten to work with some wonderful collaborators.

@Adobe
PhD/MS [interns]
Tianwei Yin, MIT
Joanna Materzynska, MIT
Yiran Xu, UMaryland
Alireza Ganjdanesh, UMaryland
Jiteng Mu, UC San Diego
Sheng-Yu Wang, CMU
Xiaojuan Wang, UWashington
Yossi Gandelsman, UC Berkeley
Yinbo Chen, UC San Diego
Nupur Kumari, CMU
Minguk Kang, POSTTECH
Dave Epstein, UC Berkeley
Gaurav Parmar, CMU
Yotam Nitzan, Tel Aviv University
Roy Or-El, UW
Lucy Chai, MIT (Fellowship winner, 2021)
Yuchen Liu, Princeton
Difan Liu, UMass Amherst
Taesung Park, UC Berkeley (Fellowship winner, 2020)
Ji Lin, MIT
William (Bill) Peebles, UC Berkeley
Alex Andonian, MIT
Utkarsh Ojha, UC Davis
Arnab Ghosh, Oxford
Minyoung (Jacob) Huh, MIT
Tamar Rott Shaham, Technion (Fellowship winner, 2020)
Peiye Zhuang, UIUC
Dima Smirnov, MIT
Noa Fish, Tel Aviv

Masters/Undergrad [interns]
Steven Liu, MIT
Seungjoo Yoo, Korea Univ (WIT scholarship winner, 2019)

PhD/MS [university collaborators]
Pranay Manocha, Princeton
Rawan Alghofaili, George Mason
Alvin Wan, UC Berkeley

 @Berkeley
Undergraduates
Xin Qin, next @ USC
Hemang Jangle
Angela S. Lin, next @ UT Austin
Xinyang Geng, next @ UC Berkeley
Tianhe Yu, next @ Stanford
Stefan A. Candra

Teaching

Introduction to Artificial Intelligence (CS 188), UC Berkeley
Graduate Student Instructor (GSI) with Prof. Anca Dragan
Spring 2017

Computer Vision (CS 280), UC Berkeley
Graduate Student Instructor (GSI) with Prof. Alexei A. Efros, Prof. Trevor Darrell
Spring 2016

Introduction to Circuits (ECE 2100), Cornell University
Teaching Assistant (TA) with Prof. Alyosha Molnar
Spring 2010

My Name

Confused by the contents of this page? Well, you may have been looking for Professor Richard Zhang or Professor Richard Zhang. My Chinese name is 章睿嘉.