We propose ZeST, a method for zero-shot material transfer to an object in the input image
given a material exemplar image. ZeST leverages existing diffusion adapters to extract …

Text-to-image diffusion models generate impressive and realistic images, but do they learn
to represent the 3D world from only 2D supervision? We demonstrate that yes, certain 3D …

Model customization introduces new concepts to existing text-to-image models, enabling the
generation of the new concept in novel contexts. However, such methods lack accurate …

The ability to edit 3D assets with natural language presents a compelling paradigm to aid in
the democratization of 3D content creation. However, while natural language is often …

Model customization introduces new concepts to existing text-to-image models, enabling the
generation of these new concepts/objects in novel contexts. However, such methods lack …

Pattern images are everywhere in the digital and physical worlds, and tools to edit them are
valuable. But editing pattern images is tricky: desired edits are often programmatic: structure …

We introduce ShapeWords, an approach for synthesizing images based on 3D shape
guidance and text prompts. ShapeWords incorporates target 3D shape information within …

Controllable text-to-image generation synthesizes visual text and objects in images with
certain conditions, which are frequently applied to emoji and poster generation. Visual text …

The Janus Problem is a common issue in SDS-based text-to-3D methods. Due to view
encoding approach and 2D diffusion prior guidance, the 3D representation model tends to …