As one of the most popular and sought-after generative models in the recent years, diffusion
models have sparked the interests of many researchers and steadily shown excellent …

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 …

We introduce Garment3DGen a new method to synthesize 3D garment assets from a base
mesh given a single input image as guidance. Our proposed approach allows users to …

Recent advancements in generative models have significantly impacted content creation,
leading to the emergence of Personalized Content Synthesis (PCS). With a small set of user …

This paper aims to generate materials for 3D meshes from text descriptions. Unlike existing
methods that synthesize texture maps, we propose to generate segment-wise procedural …

The advancement of diffusion models has pushed the boundary of text-to-3D object
generation. While it is straightforward to composite objects into a scene with reasonable …

Abstract Text-to-Image (T2I) generation has made significant advancements with the advent
of diffusion models. These models exhibit remarkable abilities to produce images based on …

In 3D modeling, designers often use an existing 3D model as a reference to create new
ones. This practice has inspired the development of Phidias, a novel generative model that …

We present MatAtlas, a method for consistent text-guided 3D model texturing. Following
recent progress we leverage a large scale text-to-image generation model (eg, Stable …

Style-guided texture generation aims to generate a texture that is harmonious with both the
style of the reference image and the geometry of the input mesh, given a reference style …