| Connelly Barnes Senior Research Scientist at Adobe |
801 N 34th St
Seattle, WA 98103
cbarnes AT adobe.com
Seattle, WA 98103
cbarnes AT adobe.com
Research Interests and Bio
I am a senior research scientist at Adobe in Seattle. My research is focused mainly on incorporating computer graphics knowledge into deep models, which do not in their naive formulation "know" a lot about graphics. My interests span a variety of computer graphics and vision topics, such as image and video processing, texture, deep learning for image tasks, brush interfaces, and compiler tools. I like to incorporate mathematical insights into research.
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.
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.
Internships
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 was previously fortunate to mentor the following interns: YiChang Shih, Jonathan Ragan-Kelley, Olga Diamanti, Soheil Darabi, Nima Kalantari, Ning Yu, Amit Raj, Noa Fish, Yi Zhou, Wei Xiong, Utkarsh Singhal, Spandan Madan, Tianshu Yu, Liqian Ma. When I was a professor, I also advised Ning Yu, Yuting Yang, Fuwen Tan, Zackary Verham, Liming Lou, ShanShan He, and Paul Nguyen. In addition, I worked with many great collaborators who are listed on my publications below.
I was previously fortunate to mentor the following interns: YiChang Shih, Jonathan Ragan-Kelley, Olga Diamanti, Soheil Darabi, Nima Kalantari, Ning Yu, Amit Raj, Noa Fish, Yi Zhou, Wei Xiong, Utkarsh Singhal, Spandan Madan, Tianshu Yu, Liqian Ma. When I was a professor, I also advised Ning Yu, Yuting Yang, Fuwen Tan, Zackary Verham, Liming Lou, ShanShan He, and Paul Nguyen. In addition, I worked with many great collaborators who are listed on my publications below.
Service
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).
Classes
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].
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.
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 (*).
Image Morphing With Perceptual Constraints and STN Alignment
Eurographics 2020
On the Continuity of Rotation Representations in Neural Networks *
CVPR 2019
Texture Mixer: A Network for Controllable Synthesis and Interpolation of Texture
CVPR 2019
Approximate Program Smoothing Using Mean-Variance Statistics, with Application to Procedural Shader Bandlimiting *
Eurographics 2018
Where and Who? Automatic Semantic-Aware Person Composition
IEEE Winter Conference on Applications of Computer Vision (WACV) 2018
Automatic Image Defect Diagnosis
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
Communications of the ACM 2018: Research Highlights
Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Losses
arXiv preprint, 2017
VizGen: Accelerating Visual Computing Prototypes in Dynamic Languages
ACM SIGGRAPH Asia 2016
Image Perforation: Automatically Accelerating Image Pipelines by Intelligently Skipping Samples
ACM Transactions on Graphics 2016 (to appear at ACM SIGGRAPH 2016)
Towards Automatic Band-Limited Procedural Shaders
Pacific Graphics 2015
PatchTable: Efficient Patch Queries for Large Datasets and Applications
ACM SIGGRAPH 2015
Synthesis of Complex Image Appearance from Limited Exemplars
ACM Transactions on Graphics 2015 (presented at ACM SIGGRAPH)
RealPigment: Paint Compositing by Example
NPAR 2014: Symposium on Non-Photorealistic Animation and Rendering
Stylized Keyframe Animation of Fluid Simulations
NPAR 2014: Symposium on Non-Photorealistic Animation and Rendering
Style Transfer for Headshot Portraits
ACM SIGGRAPH 2014
DecoBrush: Drawing Structured Decorative Patterns by Example
ACM SIGGRAPH 2014
Camouflaging an Object from Many Viewpoints
CVPR 2014 (oral presentation)
Patch-based High Dynamic Range Video
ACM SIGGRAPH Asia 2013
Halide: A Language and Compiler for Optimizing Parallelism, Locality and Recomputation in Image Processing Pipelines *
ACM PLDI 2013
Image Melding: Combining Inconsistent Images using Patch-based Synthesis
ACM SIGGRAPH 2012
The PatchMatch Randomized Matching Algorithm for Image Manipulation
Communications of the ACM: Research Highlights, 2011
PatchMatch: A Fast Randomized Matching Algorithm with Application to Image and Video
Ph.D. Dissertation, Princeton University, 2011
PatchMatch: A Randomized Correspondence Algorithm for Structural Image Editing *
ACM SIGGRAPH 2009
Video Puppetry: A Performative Interface for Cutout Animation
ACM SIGGRAPH Asia 2008
Education Publications
Enhancement of Student Learning in Experimental Design Using a Virtual Laboratory
IEEE Transactions on Education, 2008
Experiential Learning of Design of Experiments Using a Virtual CVD Reactor
American Society for Engineering Education Conference, 2006. Award for best paper in Chemical Engineering.
The Virtual CVD Learning Platform
Frontiers in Education Conference, 2006.
ThermoSolver: An Integrated Educational Thermodynamics Software Program
Undergraduate honors thesis, 2006. Oregon State University Library
Other Resources
My personal website includes other resources such as:
- Source code, including PatchMatch code and Python bindings for the Halide language.
- Artwork
- Poetry
- Writings