3Doodle: Compact Abstraction of Objects with 3D Strokes

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Choi, Changwoon, Lee, Jaeah, Park, Jaesik, Kim, Young Min
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866929530704232448
author Choi, Changwoon
Lee, Jaeah
Park, Jaesik
Kim, Young Min
author_facet Choi, Changwoon
Lee, Jaeah
Park, Jaesik
Kim, Young Min
contents While free-hand sketching has long served as an efficient representation to convey characteristics of an object, they are often subjective, deviating significantly from realistic representations. Moreover, sketches are not consistent for arbitrary viewpoints, making it hard to catch 3D shapes. We propose 3Dooole, generating descriptive and view-consistent sketch images given multi-view images of the target object. Our method is based on the idea that a set of 3D strokes can efficiently represent 3D structural information and render view-consistent 2D sketches. We express 2D sketches as a union of view-independent and view-dependent components. 3D cubic B ezier curves indicate view-independent 3D feature lines, while contours of superquadrics express a smooth outline of the volume of varying viewpoints. Our pipeline directly optimizes the parameters of 3D stroke primitives to minimize perceptual losses in a fully differentiable manner. The resulting sparse set of 3D strokes can be rendered as abstract sketches containing essential 3D characteristic shapes of various objects. We demonstrate that 3Doodle can faithfully express concepts of the original images compared with recent sketch generation approaches.
format Preprint
id arxiv_https___arxiv_org_abs_2402_03690
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle 3Doodle: Compact Abstraction of Objects with 3D Strokes
Choi, Changwoon
Lee, Jaeah
Park, Jaesik
Kim, Young Min
Computer Vision and Pattern Recognition
While free-hand sketching has long served as an efficient representation to convey characteristics of an object, they are often subjective, deviating significantly from realistic representations. Moreover, sketches are not consistent for arbitrary viewpoints, making it hard to catch 3D shapes. We propose 3Dooole, generating descriptive and view-consistent sketch images given multi-view images of the target object. Our method is based on the idea that a set of 3D strokes can efficiently represent 3D structural information and render view-consistent 2D sketches. We express 2D sketches as a union of view-independent and view-dependent components. 3D cubic B ezier curves indicate view-independent 3D feature lines, while contours of superquadrics express a smooth outline of the volume of varying viewpoints. Our pipeline directly optimizes the parameters of 3D stroke primitives to minimize perceptual losses in a fully differentiable manner. The resulting sparse set of 3D strokes can be rendered as abstract sketches containing essential 3D characteristic shapes of various objects. We demonstrate that 3Doodle can faithfully express concepts of the original images compared with recent sketch generation approaches.
title 3Doodle: Compact Abstraction of Objects with 3D Strokes
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2402.03690