801 N 34th St
Seattle, WA 98103
cbarnes AT adobe.com
Bio and Research Interests
I grew up in the beautiful Pacific Northwest, and due to my passion for the outdoors, I love it here. Feel free to see a gallery of some of my photos. I am passionate about outdoors activites such as running, kayaking, snowskiing, hiking, and mountain biking. I also like environmental protection, animal rights, whole plant foods, following lifestyle medicine guidelines, higher education and the scientific process such as encountered in doctoral programs, and living a sustainable lifestyle. Happily, Adobe does a pretty good job in terms of sustainability.

My career has focused on computer science research with numerous Adobe and academic collaborators, and particularly on algorithms used by photographers. Currently, I work mainly on computer graphics and vision topics, such as image and video processing, texture, deep learning for image tasks, and domain specific languages especially for shaders. I organize an Adobe initiative called ICE: Image Inpainting, Clean-up, and Extrapolation, where we focus on research and development related to those image editing topics. For the years 2013-2017, I was an assistant professor of computer science at the University of Virginia.

Please see my C.V. or my publications below for more information.
I will be recruiting computer science Ph.D. students for Adobe research internships, which typically result in peer-reviewed publications. If you are interested, please apply. I suggest you send myself and any other researchers with overlapping research interest an email. It helps if you can identify shared research interests. For summer internships, it also helps if you do this in November.
I have served on these technical papers committees: CGDIP (2017), Eurographics short papers (2013), Eurographics Symposium on Rendering (2013, 2014, 2017), ICCP (2013), Pacific Graphics (2017), SIGGRAPH (2015, 2016, 2019, 2020), SIGGRAPH Asia (2018, 2021).
If you are interested, you can see a list of classes that I taught when I was a professor.
Impact and Press Coverage
The PatchMatch technology that I researched for my Ph.D. was incorporated into Adobe Photoshop CS5 as content-aware fill. This received 8 million views on YouTube [1] [2], and was featured in press such as Popular Science and PC Magazine. In later Photoshop versions, Content-aware Patch, Move, and Color Adaptation were built on this technology [3]. With collaborators, I continue to work in that space.

I collaborated on the Halide project, which has been used at Adobe and Google. My collaboration on camouflage has been featured on Wired and Gizmodo, with 170,000 views on YouTube.
Research Publications (Google Scholar)
I have indicated a few of my favorite papers with asterisks (*).
GeoFill: Reference-Based Image Inpainting of Scenes with Complex Geometry
Yunhan Zhao, Connelly Barnes, Yuqian Zhou, Eli Shechtman, Sohrab Amirghodsi, Charless Fowlkes
Accepted to WACV 2023
Inpainting at Modern Camera Resolution by Guided PatchMatch with Auto-Curation
Lingzhi Zhang, Connelly Barnes, Sohrab Amirghodsi, Kevin Wampler, Eli Shechtman, Zhe Lin, Jianbo Shi
ECCV 2022
Image Inpainting with Cascaded Modulation GAN and Object-Aware Training
Haitian Zheng, Zhe Lin, Jingwan Lu, Scott Cohen, Eli Shechtman, Connelly Barnes, Jianming Zhang, Ning Xu, Sohrab Amirghodsi, Jiebo Luo
ECCV 2022
Perceptual Artifacts Localization for Inpainting
Lingzhi Zhang, Yuqian Zhou, Connelly Barnes, Sohrab Amirghodsi, Eli Shechtman, Zhe Lin, Jianbo Shi
ECCV 2022, oral presentation
Deep 360° Optical Flow Estimation by Multi-Projection Fusion
Yiheng Li, Connelly Barnes, Kun Huang, Fang-Lue Zhang
ECCV 2022
Aδ: Autodiff for Discontinuous Programs - Applied to Shaders *
Yuting Yang, Connelly Barnes, Andrew Adams, Adam Finkelstein
Learning from Shader Program Traces *
Yuting Yang, Connelly Barnes, Adam Finkelstein
Eurographics 2022. Best full paper award.
Searching for Fast Demosaicking Algorithms
Karima Ma, Michael Gharbi, Andrew Adams, Shoaib Kamil, Tzu-Mao Li, Connelly Barnes, Jonathan Ragan-Kelley
ACM Transactions on Graphics (presented at SIGGRAPH 2022)
Modulated Periodic Activations for Generalizable Local Functional Representations
Ishit Mehta, Michaël Gharbi, Connelly Barnes, Eli Shechtman, Ravi Ramamoorthi, Manmohan Chandraker
ICCV 2021
TransFill: Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transformations
Yuqian Zhou, Connelly Barnes, Eli Shechtman, Sohrab Amirghodsi
CVPR 2021
Coherent Video Generation for Multiple Hand-held Cameras with Dynamic Foreground
Fang-Lue Zhang, Connelly Barnes, Hao-Tian Zhang, Junhong Zhao, Gabriel Salas
Computational Visual Media (CVM) 2020
Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild
Liqian Ma, Zhe Lin, Connelly Barnes, Alexei A. Efros, Jingwan Lu
ECCV 2020
Image Morphing With Perceptual Constraints and STN Alignment
Noa Fish, Richard Zhang, Lilach Perry, Daniel Cohen-Or, Eli Shechtman, Connelly Barnes
Eurographics 2020
Learning to Generate Textures on 3D Meshes
Amit Raj, Cusuh Ham, Connelly Barnes, Vladimir Kim, Jingwan Lu, James Hays
CVPR Workshops: 3D WiDGET 2019. Best paper award.
Foreground-aware Image Inpainting
Wei Xiong, Jiahui Yu, Zhe Lin, Jimei Yang, Xin Lu, Connelly Barnes, Jiebo Luo
CVPR 2019
On the Continuity of Rotation Representations in Neural Networks *
Yi Zhou, Connelly Barnes, Jingwan Lu, Jimei Yang, Hao Li
CVPR 2019
Texture Mixer: A Network for Controllable Synthesis and Interpolation of Texture
Ning Yu, Connelly Barnes, Eli Shechtman, Sohrab Amirghodsi, Michal Lukáč
CVPR 2019
Approximate Program Smoothing Using Mean-Variance Statistics, with Application to Procedural Shader Bandlimiting *
Yuting Yang, Connelly Barnes
Eurographics 2018
Where and Who? Automatic Semantic-Aware Person Composition
Fuwen Tan, Crispin Bernier, Benjamin Cohen, Vicente Ordonez, Connelly Barnes
IEEE Winter Conference on Applications of Computer Vision (WACV) 2018
Automatic Image Defect Diagnosis
Ning Yu, Xiaohui Shen, Zhe Lin, Radomír Měch, Connelly Barnes
IEEE Winter Conference on Applications of Computer Vision (WACV) 2018
Halide: A Language and Compiler for Optimizing Parallelism, Locality, and Recomputation in Image Processing Pipelines
Jonathan Ragan-Kelley, Andrew Adams, Dillon Sharlet, Connelly Barnes, Sylvain Paris, Marc Levoy, Saman Amarasinghe, Frédo Durand
Communications of the ACM 2018: Research Highlights
A Survey of the State-of-the-art in Patch-based Synthesis
Connelly Barnes, Fang-Lue Zhang
Computational Visual Media 2017
Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Losses
Eric Risser, Pierre Wilmot, Connelly Barnes
arXiv preprint, 2017
VizGen: Accelerating Visual Computing Prototypes in Dynamic Languages
Yuting Yang, Samantha Prestwood, Connelly Barnes
Image Perforation: Automatically Accelerating Image Pipelines by Intelligently Skipping Samples
Liming Lou, Paul Nguyen, Jason Lawrence, Connelly Barnes
ACM Transactions on Graphics 2016 (to appear at ACM SIGGRAPH 2016)
Towards Automatic Band-Limited Procedural Shaders
Jonathan Dorn, Connelly Barnes, Jason Lawrence, Westley Weimer
Pacific Graphics 2015
PatchTable: Efficient Patch Queries for Large Datasets and Applications
Connelly Barnes, Fang-Lue Zhang, Liming Lou, Xian Wu, Shi-Min Hu
Synthesis of Complex Image Appearance from Limited Exemplars
Olga Diamanti, Connelly Barnes, Sylvain Paris, Eli Shechtman, Olga Sorkine-Hornung
ACM Transactions on Graphics 2015 (presented at ACM SIGGRAPH)
RealPigment: Paint Compositing by Example
Jingwan Lu, Stephen DiVerdi, Willa Chen, Connelly Barnes, Adam Finkelstein
NPAR 2014: Symposium on Non-Photorealistic Animation and Rendering
Stylized Keyframe Animation of Fluid Simulations
Mark Browning, Connelly Barnes, Samantha Ritter, Adam Finkelstein
NPAR 2014: Symposium on Non-Photorealistic Animation and Rendering
Style Transfer for Headshot Portraits
YiChang Shih, Sylvain Paris, Connelly Barnes, Frédo Durand, William Freeman
DecoBrush: Drawing Structured Decorative Patterns by Example
Jingwan Lu, Connelly Barnes, Connie Wan, Adam Finkelstein, Paul Asente, Radomír Měch
Camouflaging an Object from Many Viewpoints
Andrew Owens, Connelly Barnes, Alex Flint, Hanumant Singh, Bill Freeman
CVPR 2014 (oral presentation)
Patch-based High Dynamic Range Video
Nima Khademi Kalantari, Eli Shechtman, Connelly Barnes, Soheil Darabi, Dan B Goldman, Pradeep Sen
RealBrush: Painting with Examples of Physical Media
Jingwan Lu, Connelly Barnes, Stephen DiVerdi, Adam Finkelstein
Halide: A Language and Compiler for Optimizing Parallelism, Locality and Recomputation in Image Processing Pipelines *
Jonathan Ragan-Kelley, Connelly Barnes, Andrew Adams, Sylvain Paris, Frédo Durand, Saman Amarasinghe
Image Melding: Combining Inconsistent Images using Patch-based Synthesis
Soheil Darabi, Eli Shechtman, Connelly Barnes, Dan B Goldman, Pradeep Sen
The PatchMatch Randomized Matching Algorithm for Image Manipulation
Connelly Barnes, Dan B Goldman, Eli Shechtman, Adam Finkelstein
Communications of the ACM: Research Highlights, 2011
PatchMatch: A Fast Randomized Matching Algorithm with Application to Image and Video
Connelly Barnes
Ph.D. Dissertation, Princeton University, 2011
The Generalized PatchMatch Correspondence Algorithm
Connelly Barnes, Eli Shechtman, Dan B Goldman, Adam Finkelstein
ECCV 2010
Video Tapestries with Continuous Temporal Zoom
Connelly Barnes, Dan B Goldman, Eli Shechtman, Adam Finkelstein
PatchMatch: A Randomized Correspondence Algorithm for Structural Image Editing *
Connelly Barnes, Eli Shechtman, Adam Finkelstein, Dan B Goldman
Video Puppetry: A Performative Interface for Cutout Animation
Connelly Barnes, David E. Jacobs, Jason Sanders, Dan B Goldman, Szymon Rusinkiewicz, Adam Finkelstein, Maneesh Agrawala
Digital Bas-Relief from 3D Scenes
Tim Weyrich, Jia Deng, Connelly Barnes, Szymon Rusinkiewicz, Adam Finkelstein
Education Publications
Enhancement of Student Learning in Experimental Design Using a Virtual Laboratory
Milo Koretsky, Danielle Amatore, Connelly Barnes, Sho Kimura
IEEE Transactions on Education, 2008
Experiential Learning of Design of Experiments Using a Virtual CVD Reactor
Milo Koretsky, Sho Kimura, Connelly Barnes, Danielle Amatore, Derek Meyers-Graham
American Society for Engineering Education Conference, 2006. Award for best paper in Chemical Engineering.
The Virtual CVD Learning Platform
Milo Koretsky, Danielle Amatore, Connelly Barnes, Sho Kimura
Frontiers in Education Conference, 2006.
ThermoSolver: An Integrated Educational Thermodynamics Software Program
Connelly Barnes
Undergraduate honors thesis, 2006. Oregon State University Library
Other Resources
My personal website includes other resources such as: