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cs.CV2026

Render-in-the-Loop: Vector Graphics Generation via Visual Self-Feedback

Guotao Liang, Zhangcheng Wang, Juncheng Hu +5

Multimodal Large Language Models (MLLMs) have shown promising capabilities in generating Scalable Vector Graphics (SVG) via direct code synthesis. However, existing paradigms typic…

cs.CV2026

Draw2Think: Harnessing Geometry Reasoning through Constraint Engine Interaction

Juncheng Hu, Jiawei Du, Xin Zhang +1

Vision-language models solve geometry problems with rising accuracy, yet their intermediate states remain latent and unverifiable: a relation expressed in textual reasoning or draw…

cs.CV2026

VAnim: Rendering-Aware Sparse State Modeling for Structure-Preserving Vector Animation

Guotao Liang, Zhangcheng Wang, Chuang Wang +6

Scalable Vector Graphics (SVG) animation generation is pivotal for professional design due to their structural editability and resolution independence. However, this task remains c…

cs.CV2026

ArtiCAD: Articulated CAD Assembly Design via Multi-Agent Code Generation

Yuan Shui, Yandong Guan, Zhanwei Zhang +4

Parametric Computer-Aided Design (CAD) of articulated assemblies is essential for product development, yet generating these multi-part, movable models from high-level descriptions…

cs.CV2026

AmodalSVG: Amodal Image Vectorization via Semantic Layer Peeling

Juncheng Hu, Ziteng Xue, Guotao Liang +5

We introduce AmodalSVG, a new framework for amodal image vectorization that produces semantically organized and geometrically complete SVG representations from natural images. Exis…

cs.CV2026

SVGFusion: A VAE-Diffusion Transformer for Vector Graphic Generation

Ximing Xing, Juncheng Hu, Ziteng Xue +5

Generating high-quality Scalable Vector Graphics (SVGs) from text remains a significant challenge. Existing LLM-based models that generate SVG code as a flat token sequence struggl…