Easy-editable Image Vectorization with Multi-layer Multi-scale Distributed Visual Feature Embedding

Ye Chen, Zhangli Hu, Zhongyin Zhao, Yupeng Zhu, Yue Shi, Yuxuan Xiong, Bingbing Ni

Abstract:

Current parameterized image representations embed visual
information along the semantic boundaries and struggle
to express the internal detailed texture structures of image components, leading to a lack of content consistency
after image editing and driving. To address these challenges, this work proposes a novel parameterized representation based on hierarchical image proxy geometry, utilizing multi-layer hierarchically interrelated proxy geometric control points to embed multi-scale long-range structures and fine-grained texture details. The proposed representation enables smoother and more continuous interpolation during image rendering and ensures high-quality
consistency within image components during image editing.
Additionally, under the layer-wise representation strategy
based on semantic-aware image layer decomposition, we
enable decoupled image shape/texture editing of the targets
of interest within the image. Extensive experimental results
on image vectorization and editing tasks demonstrate that
our proposed method achieves high rendering accuracy of
general images, including natural images, with a significantly higher image parameter compression ratio, facilitating user-friendly editing of image semantic components.