Alive Caricature from 2D to 3D
원문 초록
Caricature is an art form that expresses subjects in abstract, simple and exaggerated view. While many caricatures are 2D images, this paper presents an algorithm for creating expressive 3D caricatures from 2D caricature images with a minimum of user interaction. The key idea of our approach is to introduce an intrinsic deformation representation that has a capacity of extrapolation enabling us to create a deformation space from standard face dataset, which maintains face constraints and meanwhile is sufficiently large for producing exaggerated face models. Built upon the proposed deformation representation, an optimization model is formulated to find the 3D caricature that captures the style of the 2D caricature image automatically. The experiments show that our approach has better capability in expressing caricatures than those fitting approaches directly using classical parametric face models such as 3DMM and FaceWareHouse. Moreover, our approach is based on standard face datasets and avoids constructing complicated 3D caricature training set, which provides great flexibility in real applications.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Structured methods for parameter inference and uncertainty quantification for mechanistic models in the life sciences
CoMPosT: Characterizing and Evaluating Caricature in LLM Simulations
Implementing measurement error models with mechanistic mathematical models in a likelihood-based framework for estimation, identifiability analysis, and prediction in the life sciences
Deep Deformable 3D Caricatures with Learned Shape Control
Dual-Domain Image Synthesis using Segmentation-Guided GAN
StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.