COMPUTER GRAPHICS RESEARCH
Computer graphics research investigates new ways to explore, visualize, and experience real and imaginary three-dimensional worlds.
The computational demands of 3D computer graphics have driven the GPU to become the most powerful processor in the world. This interdisciplinary field blends foundational math and physics with computer science, human perception, and aesthetics to create some of the most compelling images of our time. NVIDIA researchers study rendering, animation, virtual reality, and more to advance the frontiers of 3D graphics. Recent publications include:
Audio-Driven Facial Animation by Joint End-to-End Learning of Pose and Emotion, and
Towards Foveated Rendering for Gaze-Tracked Virtual Reality .
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Video Games Offer the Potential of 'Experiential Medicine'
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Faculty and researchers.
- Kavita Bala
- Donald Greenberg
- Steve Marschner
- Noah Snavely
- Ryan Benmalek
- Yen-Yu Chang
- Aditya Chetan
- Oliver Daids
- Aaron Gokaslan
- Gemmechu Hassena
- Utkarsh Mall
- Peter Michael
- Jiatian Sun
- Abe Davis and Noah Snavely Part of Cornell Research Team Receiving $1M USDA Grant for Digital Agriculture
- Accurate 3D object detection with stereo cameras in self-driving cars—without LiDAR sensors
- App creates time-lapse videos with a smartphone
- Bharath Hariharan and Noah Snavely Develop STEGO, a Novel AI Framework
- Claire Cardie and Kavita Bala Named ACM Fellows
- Cornell Graphics and Vision Group
- Cornell Program of Computer Graphics
- Bruce Walter
- Adrian Sampson
- François Guimbretière
- Ramin Zabih
Cornell is a leader in computer graphics, an interdisciplinary area that draws on many specialties including algorithms, physics, computation, psychology, computer vision, and architecture. The Cornell graphics tradition has roots going back to the earliest days of the field, when the Program of Computer Graphics (PCG) was established in 1974 and went on to make breakthrough contributions in areas including light reflection models, physics-based rendering, and visual perception for graphics. Today graphics research at Cornell flows across boundaries to cover a broad area of graphics and related topics, with research in graphics and vision in the Computer Science department , research in rendering and architecture in PCG , and research in human-computer interfaces in the Information Science program, all densely interconnected.
Current research in graphics covers a broad range of topics across the field. Examples include global illumination, scattering models, volume scattering, interactive rendering, cloth simulation, acoustics for graphics, content creation, multiview geometry, computational photography and videography, human visual perception, and appearance capture. Our research addresses applications ranging from visual effects, animation, and games to architecture, surgery simulation, advertising, photography, and photo browsing.
Kavita Bala specializes in computer graphics and computer vision, leading research in visual recognition, search, and discovery; material modeling and acquisition, physically-based rendering; and material perception. In her computer graphics research she uses knowledge of human perception to develop new rendering algorithms for large-scale models for architectural visualization, and new algorithms for material acquisition and representation of complex materials like cloth. In her computer vision research, she develops algorithms for material recognition, fine-grained visual search for products in ecommerce, and large-scale visual discovery for planet-wide events, from global fashion discovery to event detection of forest fires in satellite imagery. Applications of her work include virtual prototyping, sustainability, virtual-reality training, architectural planning, and e-commerce.
Donald Greenberg , the founder of the Program of Computer Graphics , has been researching and teaching in the field of computer graphics from 1966. During the last 15 years, he has been primarily concerned with research advancing the state-of-the-art in computer graphics and with utilizing these techniques as they may be applied to a variety of disciplines. His specialities include hidden surface algorithms, geometric modeling, color science, and realistic image generation. Donald Greenberg is the Jacob Gould Schurman Professor of Computer Graphics and the Director of the Program of Computer Graphics.
Abe Davis works on a range of topics in graphics, vision, and HCI, with a focus on how to apply work in these fields to new problems and application spaces. His work ranges across video and image analysis, photography, video editing, augmented reality, and computational fabrication, with applications from civil engineering to video editing and scene modeling to quilting.
Steve Marschner works on modeling materials for graphics , ranging from their optics to thier mechanics, often using techniques that draw from computer vision. For rendering, material modeling is the fundamental problem of understanding and simulating the interaction of light with materials. Recent work has focused on models for the materials that are important for realistic virtual characters—skin, cloth, hair—as well as other materials with complex three-dimensional structure. These materials can often be rendered as volumes of structured, translucent material. Optics works together with shape and motion to define the appearance of a material, so another focus is on realistic models for the mechanics of materials, particularly cloth.
Noah Snavely is primarily interested in analyzing large image collections to automatically recover the geometry and appearance of real-world scenes, and in using this derived structure to create better visualizations of photo collections and 3D scenes. Noah is particularly interested in leveraging the vast, rich collections of imagery available on the Internet to recreate the world in 3D. This research encompasses problems in both computer vision and computer graphics, including structure from motion, multi-view stereo, graph algorithms for analyzing large image collections, image-based rendering, and 3D navigation interfaces. Noah is also interested in creating systems and techniques that make it simple to create 3D models using a hand-held camera.
Research in computer graphics at Yale includes sketching, alternative design techniques, texture models, the role of models of human perception in computer graphics, recovering shape and reflectance from images, computer animation, simulation, and geometry processing. Applications that drive this work are architectural design, cultural heritage documentation and analysis, the study of biological forms, as well as traditional targets such as feature films, games, and other visual media. Computer graphics is one of the disciplines within Yale C2 (Creative Consilience of Computing and the Arts).
Computer graphics is used extensively in a wide range of domains—from feature film and games to medical visualization and financial analysis. However impressive the growth of computer graphics applications has been over the past forty years, the goal of easily authoring computer graphics models input remains elusive. At Yale, the research in modeling includes sketching systems for early conceptual design and the capture and editing of digital models of existing physical objects at a range of scales—from entire buildings to individual objects.
Computer graphics models need to include material appearance properties as well as geometry. Unfortunately, the models widely used in computer graphics assume that the materials are both pristine and immutable, even though real materials are neither. The goal of research on material and texture models at Yale is to devise new material representations and expressive interfaces for editing such representations, to develop novel methods to simulate materials and the processes that affect their appearance, and to physically measure the input required for material models.
Realistic, expressive motion remains an ongoing challenge in computer graphics. In order to generate animations that are both visually convincing and narratively compelling, the animation research at Yale examines new methods for computing the physics that underlie natural phenomena such as rising smoke, splashing water, and the forces that form the characteristic shapes of skin and muscle under human movement. While realism is important, expressivity and artistic directability play an equally key role, and distilling the exact parameters that capture an effective performance remains an open area of research.
Faculty working in this area:
Highlights in this area:.
- Adobe Research
Research trends: The future of computer graphics—and the tools we’ll use to create them
March 28, 2022, tags: graphics (2d & 3d).
Wondering which trends and ideas will shape technology in 2022 and beyond? We talked to a few members of the Adobe Research team to find out.
Nathan Carr, an Adobe Research Senior Principal Scientist with a focus on computer graphics, gave us a peek into the future of 2D and 3D imaging. He also shared his vision for how we’ll interact with creative tools in the future.
Can you tell us about a trend you’re following in 2022?
One popular trend is the development of new representations for 3D assets. In the past we used to store things in the form of triangles and surface patches. In this new trend, we’re looking at neural representations to come up with new forms of information that compress and compact material, appearance, and geometry into one single optimized form that can be displayed and manipulated.
You can think of this as a next-generation 3D photograph. It’s a way to capture and represent the shape and appearance of the world so that we can start interacting with it in a deeper, richer way. I think these new representations will open a lot of exciting opportunities. High-end effects like raytracing are now being used in games to bring an unprecedented level of visual quality. I wonder whether a new evolution in rendering is about to take place that mixes light transport simulation with machine learning to produce photorealistic imagery even more efficiently.
What do you hope researchers can accomplish this year?
One thing I’m thinking about deeply is the emergence of algorithms that will transform how we operate with computers. I think we want to move to a place where humans are interacting with computers in their own language and leveraging intuition about the world, rather than forcing humans to operate in the language of computers.
We’ve seen this trend over time. I think it will accelerate, and this has some deep ramifications. For example, today there’s a huge learning curve that artists go through to understand how computers represent things. In particular, 3D design software is incredibly complex, taking years to master. Now we’re starting to be able to train algorithms that enable computers to meet humans in their own frame of mind, which will democratize creative tools so more people can access them. Computers will operate in a collaborative manner, anticipating and assisting in very complex tasks with high-level guidance from humans. With these new systems, artists and creatives will be able to produce content more efficiently while being more expressive.
What do you think people will be talking about at conferences and in papers this year?
As we talk about computers operating in the language of humans, we’ll need to collect a lot of data about the world.
For example, classically, we have represented images or 3D objects in very primitive forms without any extra information. So you can look at the colors and try to guess what pictures are, or if it’s a 3D triangle mesh, you can look at the shape of the geometry, but there’s only so much information there.
But if you pair this with a knowledge base of what is in millions of photos, or if you have huge collections of 3D shapes that people have authored and you know what their semantic meanings and relationships are, then suddenly you can apply that learning to unlock a lot of new capabilities. I think we’ll be talking about this transformation.
Which trends are you excited about beyond your field?
Hardware trends are exciting because a lot of what we do with machine learning and AI is often limited by hardware and compute. Even when we manage to train useful AI algorithms, we often struggle to deploy them on low-power devices because there just isn’t the hardware capability. This, however, is changing rapidly.
As a computer graphics research scientist, it used to be that you just needed one nice computer and a compiler, and you could do your work. Now you need a cluster or a supercomputer at your beck and call to train the latest machine learning algorithms. So how does this scale to every developer and creator? The power budgets are not on a sustainable path and need addressing. This will require not just innovations in hardware, but a co-evolution of the software algorithms behind machine learning models.
I also wonder about new forms of “fuzzy” computing (e.g., quantum computing) where we might be willing to tolerate a little bit of imprecision or uncertainty in an answer. If this form of computing can execute magnitudes faster with lower power requirements and reasonable accuracy, it may be worth the trade-off. These new processors may require an entire reinvention of the algorithms we use and changes in the ways we write code. Regardless, being able to train models at scale with massive data and deploy them will require deep ingenuity. I believe such issues will be at the forefront of computing over the next decade.
Wondering what’s going on in 2D and 3D graphics at Adobe Research? You can learn more here .
Research trends: the way we watch videos is changing, and so are the tools we use to create them, vishy swaminathan, a senior principal scientist at adobe research, works on next-generation video and digital experiences., research trends: what’s next for human-computer interaction in the metaverse and beyond, cuong nguyen, research scientist, studies human-computer interaction, virtual reality (vr), augmented reality (ar), and the future of content creation and collaboration technologies., from stylized animation to perfect poses to customized fonts: adobe research sneaks at max 2021, sneaks—those quick peeks at still-in-development-technology from adobe — are always one of the highlights of max, and 2021 did not disappoint..
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Computer Graphics, Vision, AR/VR, Animation & Game Science
The GRAIL group is known for ground-breaking research in computational photography, games for science and education, 3-D reconstruction, Internet photo collections, object recognition, human shape and motion analysis, information visualization, and animation. In addition to benefiting from the expertise of our core faculty members, our students interact with world-class researchers from Microsoft Research, Adobe, Intel, and Google. Recent projects include Moving Portraits , which generates face animations of a person from large image collections and has been widely deployed as the “Face Movies” feature in Google’s Picasa, and Illumination-Aware Age Progression , which automatically renders images of a child’s face at multiple ages throughout his/her lifetime.
The UW Reality Lab brings together researchers to focus on augmented and virtual reality in order to advance the state-of-the-art and to educate the next generation of researchers and practitioners. Founded in 2018, it supports diverse research projects in the areas of computer vision, computer graphics, display optics, 3D reconstruction, lightfield rendering, accessibility, character animation, input devices, and more. Other ongoing programs include an idea incubator, courses , The Reality Studio , and The Reality Lab Lectures . Examples of work from UW Reality Lab Researchers include: Soccer On Your Tabletop , a system for turning 2D video of sports matches into 3D AR experiences, a Near-Eye Visor design that projects onto a micron-scale thick metasurface to allow a greater field of view; and an inexpensive way to turn a 2D tablet into a 3D display device.
Researchers at UW CSE's Center for Game Science use gaming to solve grand challenges, crowdsource human problem-solving to aid scientific discovery, and improve student interest and achievement in mathematics. Noteworthy projects include Foldit , the award-winning game that has engaged more than 100,000 players around the world in helping scientists to understand the 3-D structure of proteins to combat viruses such as AIDS and Ebola, and Nanocrafter , a new game that enables players to build nanoscale machines using small pieces of DNA to advance synthetic biology research.
The Animation Research Labs is a multi-disciplinary effort that brings together faculty and students from UW CSE, the Department of Architecture , and the Schools of Art , DXARTS , Drama , and Music .The ARL is focused on advancing the state-of-the-art in animation through teaching, research, and computer-animated production in collaboration with experts from Disney Animation Studios, Bungie, Industrial Light & Magic, Microsoft Game Studios, Pixar, and many others.
COMPUTER GRAPHICS RESEARCH Computer graphics research investigates new ways to explore, visualize, and experience real and imaginary three-dimensional worlds. The computational demands of 3D computer graphics have driven the GPU to become the most powerful processor in the world.
Computer Graphics. Read the latest news in computer graphics, 3-D imaging and more. ... 2022 — A research team has developed a display which projects holographic images that change color and ...
Steve Marschner works on modeling materials for graphics, ranging from their optics to thier mechanics, often using techniques that draw from computer vision. For rendering, material modeling is the fundamental problem of understanding and simulating the interaction of light with materials.
Computer Graphics Research in computer graphics at Yale includes sketching, alternative design techniques, texture models, the role of models of human perception in computer graphics, recovering shape and reflectance from images, computer animation, simulation, and geometry processing.
As a computer graphics research scientist, it used to be that you just needed one nice computer and a compiler, and you could do your work. Now you need a cluster or a supercomputer at your beck and call to train the latest machine learning algorithms. So how does this scale to every developer and creator?
The Animation Research Labs is a multi-disciplinary effort that brings together faculty and students from UW CSE, the Department of Architecture, and the Schools of Art, DXARTS, Drama, and Music.The ARL is focused on advancing the state-of-the-art in animation through teaching, research, and computer-animated production in collaboration with ...