We address the challenges of precise image inversion and disentangled image editing in
the context of few-step diffusion models. We introduce an encoder based iterative inversion …

We propose Magic Clothing, a latent diffusion model (LDM)-based network architecture for
an unexplored garment-driven image synthesis task. Aiming at generating customized …

Text-driven diffusion models have significantly advanced the image editing performance by
using text prompts as inputs. One crucial step in text-driven image editing is to invert the …

We study text-based image editing (TBIE) of a single image by counterfactual inference
because it is an elegant formulation to precisely address the requirement: the edited image …

Despite significant strides in the field of 3D scene editing, current methods encounter
substantial challenge, particularly in preserving 3D consistency in multi-view editing …

Image editing aims to edit the given synthetic or real image to meet the specific requirements
from users. It is widely studied in recent years as a promising and challenging field of …

Despite recent advances in UNet-based image editing, methods for shape-aware object
editing in high-resolution images are still lacking. Compared to UNet, Diffusion Transformers …

This is the technique report for the winning solution of the CVPR2024 GenAI Media
Generation Challenge Workshop's Instruction-guided Image Editing track. Instruction-guided …

Abstract In 3D Artificial Intelligence Generated Content (AIGC), compared with generating
3D assets from scratch, editing extant 3D assets satisfies user prompts, allowing the creation …

Video Diffusion Models have been developed for video generation, usually integrating text
and image conditioning to enhance control over the generated content. Despite the …