This work presents AnyDoor a diffusion-based image generator with the power to teleport
target objects to new scenes at user-specified locations with desired shapes. Instead of …

The pursuit of controllability as a higher standard of visual content creation has yielded
remarkable progress in customizable image synthesis. However, achieving controllable …

Recent large-scale generative models learned on big data are capable of synthesizing
incredible images yet suffer from limited controllability. This work offers a new generation …

Instruction-based image editing holds immense potential for a variety of applications as it
enables users to perform any editing operation using a natural language instruction …

Advancing image inpainting is challenging as it requires filling user-specified regions for
various intents, such as background filling and object synthesis. Existing approaches focus …

We propose\textbf {DMV3D}, a novel 3D generation approach that uses a transformer-based
3D large reconstruction model to denoise multi-view diffusion. Our reconstruction model …

Object compositing based on 2D images is a challenging problem since it typically involves
multiple processing stages such as color harmonization, geometry correction and shadow …

Denoising diffusion models have emerged as a powerful tool for various image generation
and editing tasks, facilitating the synthesis of visual content in an unconditional or input …

Many existing adversarial attacks generate-norm perturbations on image RGB space.
Despite some achievements in transferability and attack success rate, the crafted adversarial …

We introduce a new task--language-driven video inpainting which uses natural language
instructions to guide the inpainting process. This approach overcomes the limitations of …