Invited speaker #2
Canva
Talk title and abstract
Reimagining Design Intelligence: The Layer Is Where
Co-Creation Begins
A flat image is where co-creation ends; a layered design
is where it begins.
Today's generative models produce stunning pictures — but
a picture of a design is not a design. Real designs are
layered, structured, and editable; real creation is
iterative, with intent that evolves as people make.
Co-creation therefore demands outputs humans can take over
at any moment: representations that preserve authorship
instead of locking people out of their own work.
In this talk, I will share our team's journey toward
design-native intelligence along three threads. Generation:
ART introduces variable multi-layer transparent image
generation, MRT unifies text-to-layer, image-to-layer, and
layer-to-layer generation in a single model, and PixelART
shows that image-to-layer decomposition can be learned
directly in pixel space — with neither a VAE nor T2I
pretraining. Understanding: DAD (Detect Anything in
Graphic Design) parses the world's existing flat designs
back into editable elements, letting AI meet creators where
their content already lives. Restyling: ReChart transfers
visual style across charts while preserving the underlying
data and layout, treating editing as a first-class
generative task.
Several of these capabilities already ship in products used
by millions of creators. Together, they converge on
design-native foundation models that generate, understand,
and edit designs in their native layered form — turning
generative AI from a picture generator into a genuine
co-creator of living design documents.
Yuhui (Ryan) Yuan is a Research Director at Canva CORE and the
founder of Canva Research Lab in China, where he leads a
research team focused on building next-generation graphic
design foundation models. His current work centers on frontier
multimodal generation, multi-layer visual content generation,
and graphic design editing models, with the goal of advancing
AI systems that can transform how people create and edit
visual content.
Before joining Canva, he spent eight years at Microsoft as a
Senior Researcher, working on cutting-edge computer vision
problems including semantic segmentation, object detection,
scene understanding, document intelligence, and generative AI
applications. Several of his research contributions have been
integrated into Microsoft products, including Azure Form
Recognizer and Microsoft Designer.
Ryan received his Ph.D. in Computer Vision from the University
of Chinese Academy of Sciences, where he worked on semantic
segmentation, and his M.S. in Computer Science from Peking
University. His representative research includes works such as
OCNet, OCRNet, HDETR, Glyph-ByT5, SPO, and ART, as well as
publications in top venues including ICCV, ECCV, IJCV, and
ICLR.