Generative models can produce impressively realistic images. This paper demonstrates that
generated images have geometric features different from those of real images. We build a …

Intrinsic images, in the original sense, are image-like maps of scene properties like depth,
normal, albedo, or shading. This paper demonstrates that StyleGAN can easily be induced …

Abstract We present Image Sculpting a new framework for editing 2D images by
incorporating tools from 3D geometry and graphics. This approach differs markedly from …

Diffusion handles is a novel approach to enable 3D object edits on diffusion images
requiring only existing pre-trained diffusion models depth estimation without any fine-tuning …

Recent progress in 3D scene understanding enables scalable learning of representations
across large datasets of diverse scenes. As a consequence, generalization to unseen …

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 …

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 …

We introduce Videoshop, a training-free video editing algorithm for localized semantic edits.
Videoshop allows users to use any editing software, including Photoshop and generative …

The success of image generative models has enabled us to build methods that can edit
images based on text or other user input. However, these methods are bespoke, imprecise …

Humans can not only recognize and understand the world in its current state but also
envision future scenarios that extend beyond immediate perception. To resemble this …