Jordan Novella's process is rooted in new movements including climate justice, liberation, and economic freedom, employing oils, mixed media, photography, and video arts. While seeking out new genres, she remains rooted in certain traditions of Latvian gnosis, New Forest Commoners, and widgie subculture. Solo shows include "Sneaker Closure" in 2018 at the Into Black Gallery, "Dream About You" at Jetstream Square in 2019, and a virtual exhibition in 2020 called "Chance Stage." She has also shown at a number of group shows, and is a multi-instrumentalist in numerous musical acts, including Glass Calling, Repeat Boys, and Uber Beats. In fall of 2021 she is slated to be the next artist-in-residence at Corson's Inlet State Park.
The workshop on Machine Learning for Content Creation (MLCC) aims at bringing together researchers and practitioners from Machine Learning, Computer Vision, and Graphics, with an emphasis on content creation. The goal of this workshop is to facilitate the sharing of information and practices, as well as finding bridges between these communities and promoting discussion.
MLCC will be a two-day workshop, with one day in the Bay Area (Los Gatos), California, and one day in Los Angeles. Participants have the option of attending either or both of the two days in person.
Organizers:
Hossein Taghavi - mtaghavi@netflix.com
Vi Iyengar - vramaswamy@netflix.com
Paul Debevec - debevec@netflix.com
Don't hesitate to contact us for any information: mlcc-organizers@netflix.com
Angjoo Kanazawa is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of California at Berkeley. Her research is at the intersection of Computer Vision, Computer Graphics, and Machine Learning, focusing on the visual perception of the dynamic 3D world behind everyday photographs and video. Previously, she was a research scientist at Google NYC with Noah Snavely, and prior to that she was a BAIR postdoc at UC Berkeley advised by Jitendra Malik, Alyosha Efros, and Trevor Darrell.
She completed her PhD in Computer Science at the University of Maryland, College Park with her advisor David Jacobs. She also spent time at the Max Planck Institute for Intelligent Systems with Michael Black. She has been named a Rising Star in EECS and is a recipient of Anita Borg Memorial Scholarship, Best Paper Award in Eurographics 2016 and the Google Research Scholar Award 2021. She also serves on the advisory board of Wonder Dynamics, whose goal is to utilize AI technologies to make VFX effects more accessible for indie filmmakers.
Orazio is a Principal Research Scientist and Tech Lead at NVIDIA Research. His research focuses on content capture and novel view synthesis, efficient low-level computer vision, and computational photography. His previous inventions also include algorithms to overcome the limitations of regular cameras, and new paradigms pictures can be captured, processed, and consumed by photographers. Orazio is also a senior associate editor of the IEEE Transactions of Computational Imaging.
Paul Debevec is Netflix’s Director of Research for Creative Algorithms and Technology where he oversees R&D in new technologies in computer vision, computer graphics, and machine learning with applications in visual effects, virtual production, and animation. His 2002 Light Stage 3 system at the USC Institute for Creative Technologies introduced the technique of surrounding actors with LEDs to light them with images of virtual sets virtual production. Techniques from Paul’s work have been used to create key visual effects sequences in The Matrix, Spider-Man 2, Benjamin Button, Avatar, Gravity, Furious 7, Blade Runner: 2049, Gemini Man, Free Guy, numerous video games, and to record a 3D Portrait of US President Barack Obama. His light stage facial capture technology has helped numerous technology companies, video game studios, and visual effects companies create photoreal digital actors and advance ML datasets for facial appearance. Paul’s work in HDR imaging, image-based lighting, and light stage facial capture has been recognized with two technical Academy Awards and SMPTE’s Progress Medal. Paul is a Fellow of the Visual Effects Society and a member of the Television Academy's Science and Technology Peer Group, and has served on the Motion Picture Academy's Visual Effects Executive Committee and Science and Technology Council, and as Vice President of ACM SIGGRAPH. More info at: www.debevec.org.
Ravi Ramamoorthi is the Ronald L. Graham professor of Computer Science at the University of California, San Diego, and founding Director of the UC San Diego Center for Visual Computing. He received his Ph.D. at Stanford in 2002, and earlier held tenured faculty positions at Columbia University and UC Berkeley. Prof. Ramamoorthi is an author of more than 150 refereed publications in computer graphics and computer vision, including 85+ at ACM SIGGRAPH/TOG, and has played a key role in building multi-faculty research groups that have been recognized as leaders in computer graphics and computer vision at Columbia, Berkeley and UCSD. His research has been recognized with a half-dozen early career awards, including the ACM SIGGRAPH Significant New Researcher Award in computer graphics in 2007, and the Presidential Early Career Award for Scientists and Engineers (PECASE) for his work in physics-based computer vision in 2008. He was elevated to IEEE and ACM Fellow in 2017, and inducted into the SIGGRAPH Academy in 2019.
Prof. Ramamoorthi's work has had substantial impact in industry, with techniques like spherical harmonic lighting being adopted in industry-standard RenderMan software, and widely used in interactive applications and movie productions. He has graduated more than 20 postdoctoral, Ph.D. and M.S. students, many of whom have taken positions at leading universities or research labs and won leading fellowships and awards, including the ACM SIGGRAPH Doctoral Dissertation Award. He has also taught the first open online course in computer graphics as one of the first nine classes on the edX platform, with more than 100,000 registrations to date and a Chinese translation available via XuetangX. He (and his course) received an inaugural edX Prize certificate for this effort in 2016 and again in 2017, as the only computer science recipient and only course to be recognized twice.
Ben Grossmann is co-founder of Magnopus, a company bridging the physical and digital worlds with more than 170 artists, designers, and engineers in Los Angeles and London. He is an Academy Award-winning and Emmy Award-winning visual effects supervisor and virtual production supervisor in film, television, VR, & AR. Most recently he was project director of the world’s largest social digital twin at Expo 2020 Dubai for tens of millions of visitors.
Pietro Perona received a Ph.D. in electrical engineering and computer science from the University of California, Berkeley, in 1990. From 1990 to 1991, he was a postdoctoral fellow at the Massachusetts Institute of Technology in the Laboratory for Information and Decision Systems. In the fall of 1991, Perona joined the California Institute of Technology as assistant professor. He became full professor in 1996 and the Allen E. Puckett Professor of Electrical Engineering and Computation and Neural Systems in 2006. From 1999 to 2005, Perona was the director of the National Science Foundation Center for Neuromorphic Systems Engineering. From 2005 to 2016, he led the Computation and Neural Systems program at the California Institute of Technology.
Perona’s research focuses on the computational aspects of vision and learning. He is known for the anisotropic diffusion equation, a partial differential equation that filters image noise while enhancing region boundaries. He is currently interested in visual recognition and in visual analysis of behavior. In the early 2000s, Perona pioneered the study of visual categorization. Currently, in collaboration with colleagues Markus Meister and David Anderson, he applies machine vision to measuring and analyzing the behavior of laboratory animals as they learn complex tasks and as the engage in social behavior.
Perona is the recipient of the 2013 Longuet-Higgins Prize, the 2010 Koenderink Prize and the 2021 PAMI Distinguished Researcher Award for fundamental contributions in computer vision. He is the recipient of the 2003 CVPR best paper award. He is also the recipient of a 1996 NSF Presidential Young Investigator Award.
Ryan Laney is the Visual Effects Supervisor at Teus Media, a small shop founded to provide visual effects to documentaries. He has been using visual effects to support storytelling in movies and special interest projects since 1994. He learned the trade working with amazing teams at Manex, ILM, Digital Domain, and Imageworks where he had the opportunity to be involved with facility projects, and to develop ground-up effects pipeline builds on many major motion pictures.
In recent years he has been breaking new ground in the crossover between visual effects and documentary filmmaking. The digital veils he produced for Welcome To Chechnya earned the film a Visual Effects Society Nomination for Supporting Visual Effects and a spot on the Oscars’ VFX Shortlist, the first documentary to make either list. The focus on machine learning techniques to protect identities of contributors has led to working with human rights groups and efforts to make MLCC tools available to more filmmakers.
Dr. Yajie Zhao is a computer scientist at USC Institute for Creative Technologies (USC-ICT) and she is also the acting director of the Vision and Graphics Lab of USC-ICT. Yajie received her Bachelor's degree in Computer Science from Xi'an Jiaotong University and earned her Ph.D. degree in 2017 from the University of Kentucky. Her research interests are high-quality 3D content creation, which includes human digitization, performance capturing, and scene reconstruction/understanding. In particular, Yajie is leading the lab to pursue high-resolution human face/body 3D representation, neural rendering, and human/scene-related applications in VR/AR.
Jernej Barbič is a full professor of computer science at USC. He has published over 40 academic publications in top venues in computer graphics and related fields. Jernej is also a co-founder and CTO of a successful computer animation startup company "Ziva Dynamics" (acquired by Unity Technologies), whereby he contributed technical and business leadership on real-time character deformation, anatomically based modeling, nonlinear elasticity and digital humans. In 2014, he was named a Sloan Research Fellow. In 2011, MIT Technology Review named him one of the Top 35 Innovators under the age of 35 in the world (TR35). Jernej is also the author of Vega FEM, a free C/C++ software physics library for deformable object simulation. He received his Ph.D. from CMU, and did postdoctoral research at MIT CSAIL. His interests include computer graphics, animation, interactive physics, haptic rendering, visual effects for film, medical simulation, FEM deformable objects, biomechanics, intellectual property law and startup companies.
Boris Chen is a machine learning engineer at Netflix. He received his B.S. in Applied Mathematics from the California Institute of Technology in 2008, and M.S.E. in Operations Research and Financial Engineering from Princeton University in 2012. His research career started in understanding theoretical limitations of convex learning methods with noisy datasets, but has since become interested in building machine learning driven applications. His current work focuses on video understanding and developing new tools to help artwork and video creatives make more engaging content.
