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Sketchformer++:A hierarchical transformer architecture for vector sketch representationOA

中文摘要

With the rising ubiquity of digital touch devices and sketch-based interfaces,freehand sketching has become an essential mode of visual communication.Nevertheless,interpreting these often ambiguous and sparse sketches poses challenges for computers.This paper presents Sketchformer++,a hierarchical transformer architecture for the neural representation of vector sketches.It treats a vector sketch as a three-level structure,at sketch level,stroke level,and segment level.Three self-attention modules are adopted in the network architecture,corresponding to the sketch hierarchy.The semantics of sketches are aggregated from local to global levels,resulting in neural representations of sketches.Extensive experiments show that Sketchformer++helps to achieve superior performance in various downstream tasks,including sketch reconstruction,sketch recog-nition,sketch semantic segmentation,and sketch retrieval,demonstrating its robustness and effectiveness as a means of sketch representation.Code is available at https://github.com/BHR7/SketchformerPlus.

Pengfei Xu;Banhuai Ruan;Youyi Zheng;Hui Huang

College of Computer Science and Software Engineering,Shenzhen University,Shenzhen 518060,ChinaCollege of Computer Science and Software Engineering,Shenzhen University,Shenzhen 518060,ChinaState Key Lab of CAD&CG,Zhejiang University,Hangzhou 310058,ChinaCollege of Computer Science and Software Engineering,Shenzhen University,Shenzhen 518060,China

信息技术与安全科学

vector sketchtransformerhierarchyneural representationsketch recognitionsketch semantic segmentationsketch retrieval

《Computational Visual Media》 2026 (1)

P.173-188,16

supported in part by the National Natural Science Foundation of China(62472287,62072316,62172363,U21B2023)Natural Science Foundation of Shenzhen City(JCYJ20250604181519025)Department of Education of Guangdong Province Innovation Team(2022KCXTD025)Shenzhen Science and Technology Program(KQTD20210811090044003)Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ).

10.26599/CVM.2025.9450456

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