ProEdit: Simple Progression is All You Need for High-Quality 3D Scene Editing
원문 초록
This paper proposes ProEdit - a simple yet effective framework for high-quality 3D scene editing guided by diffusion distillation in a novel progressive manner. Inspired by the crucial observation that multi-view inconsistency in scene editing is rooted in the diffusion model's large feasible output space (FOS), our framework controls the size of FOS and reduces inconsistency by decomposing the overall editing task into several subtasks, which are then executed progressively on the scene. Within this framework, we design a difficulty-aware subtask decomposition scheduler and an adaptive 3D Gaussian splatting (3DGS) training strategy, ensuring high quality and efficiency in performing each subtask. Extensive evaluation shows that our ProEdit achieves state-of-the-art results in various scenes and challenging editing tasks, all through a simple framework without any expensive or sophisticated add-ons like distillation losses, components, or training procedures. Notably, ProEdit also provides a new way to control, preview, and select the "aggressivity" of editing operation during the editing process.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
WeatherEdit: Controllable Weather Editing with 4D Gaussian Field
Is Diversity All You Need for Scalable Robotic Manipulation?
EAMamba: Efficient All-Around Vision State Space Model for Image Restoration
FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language
These are Not All the Features You are Looking For: A Fundamental Bottleneck In Supervised Pretraining
Visual-Instructed Degradation Diffusion for All-in-One Image Restoration
토론
이 논문과 연결된 포럼 글이 아직 없습니다.