Scalable Vector Graphics (SVG) are ubiquitous in modern 2D interfaces due to their ability to scale to different resolutions. However, despite the success of deep learning-based models applied to rasterized images, the problem of vector graphics representation learning and generation remains largely unexplored. In this work, we propose a novel hierarchical generative network, called DeepSVG, for complex SVG icons generation and interpolation. Our architecture effectively disentangles high-level shapes from the low-level commands that encode the shape itself. The network directly predicts a set of shapes in a non-autoregressive fashion. We introduce the task of complex SVG icons generation by releasing a new large-scale dataset along with an open-source library for SVG manipulation. We demonstrate that our network learns to accurately reconstruct diverse vector graphics, and can serve as a powerful animation tool by performing interpolations and other latent space operations. Our code is available at https://github.com/alexandre01/deepsvg.
LINR Bridge: Vector Graphic Animation via Neural Implicits and Video Diffusion Priors
Wangxuan Institute of Computer Technology, State Key Laboratory of Multimedia Information Processing, \ University, Beijing, China；Wangxuan Institute of Computer Technology, State Key Laboratory of Multimedia Information Processing, Peking University, Beijing, China
VAnim: Rendering-Aware Sparse State Modeling for Structure-Preserving Vector Animation
School of Software, Beihang University, Beijing, China（北京航空航天大学软件学院）；Department of Computer Science, The University of Hong Kong, Hong Kong, China（香港大学计算机科学系）；College of Computer Science and Technology, Zhejiang University, Hangzhou, China（浙江大学计算机科学与技术学院）
InternSVG: Towards Unified SVG Tasks with Multimodal Large Language Models
Shanghai Jiao Tong University（上海交通大学）；Shanghai AI Laboratory（上海人工智能实验室）；Nanjing University（南京大学）；Donghua University（东华大学）；The Chinese University of Hong Kong（香港中文大学）
DesignAsCode: Bridging Structural Editability and Visual Fidelity in Graphic Design Generation
School of Software and Microelectronics, Peking University, Beijing, China（软件与微电子学院，北京大学，北京，中国）；Microsoft（微软公司）；ShanghaiTech University, Shanghai, China（上海交通大学，上海，中国）
Generative Visual Communication in the Era of Vision-Language Models
Raymond and Beverly Sackler Faculty of Exact Sciences（雷蒙德和贝弗利·萨克勒精密科学学院）；Blavatnik School of Computer Science（布拉瓦尼克计算机科学学院）；School of Computer Science at Tel Aviv University（特拉维夫大学计算机科学学院）
