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Related papers: SVGDreamer: Text Guided SVG Generation with Diffus…

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Vector graphics are widely used to represent fonts, logos, digital artworks, and graphic designs. But, while a vast body of work has focused on generative algorithms for raster images, only a handful of options exists for vector graphics.…

Computer Vision and Pattern Recognition · Computer Science 2021-04-02 Pradyumna Reddy , Michael Gharbi , Michal Lukac , Niloy J. Mitra

We introduce LiveSVG, a zero-shot approach for generating Scalable Vector Graphics (SVG) animations using video diffusion models. Current SVG animation methods struggle with complex motions: LLM-based code synthesis fails to express fine,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Matan Levy , Ran Margolin , Bar Cavia , Dvir Samuel , Yael Pritch , Shmuel Peleg , Alex Rav Acha , Ariel Shamir , Dani Lischinski

In this paper, we propose an effective two-stage approach named Grounded-Dreamer to generate 3D assets that can accurately follow complex, compositional text prompts while achieving high fidelity by using a pre-trained multi-view diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Xiaolong Li , Jiawei Mo , Ying Wang , Chethan Parameshwara , Xiaohan Fei , Ashwin Swaminathan , CJ Taylor , Zhuowen Tu , Paolo Favaro , Stefano Soatto

Text-to-3D generation aims to create 3D assets from text-to-image diffusion models. However, existing methods face an inherent bottleneck in generation quality because the widely-used objectives such as Score Distillation Sampling (SDS)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-24 Zixuan Chen , Ruijie Su , Jiahao Zhu , Lingxiao Yang , Jian-Huang Lai , Xiaohua Xie

Generated Scalable Vector Graphics (SVG) images demand evaluation criteria tuned to their symbolic and vectorial nature: criteria that existing metrics such as FID, LPIPS, or CLIPScore fail to satisfy. In this paper, we introduce SVGauge,…

While text-to-3D and image-to-3D generation tasks have received considerable attention, one important but under-explored field between them is controllable text-to-3D generation, which we mainly focus on in this work. To address this task,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Zhiqi Li , Yiming Chen , Lingzhe Zhao , Peidong Liu

Existing text-based 3D generation methods generate attractive results but lack detailed geometry control. Sketches, known for their conciseness and expressiveness, have contributed to intuitive 3D modeling but are confined to producing…

Graphics · Computer Science 2024-05-15 Feng-Lin Liu , Hongbo Fu , Yu-Kun Lai , Lin Gao

We introduce VectorGym, a comprehensive benchmark suite for Scalable Vector Graphics (SVG) that spans generation from text and sketches, complex editing, and visual understanding. VectorGym addresses the lack of realistic, challenging…

Recent advancements in text-to-3D generation improve the visual quality of Score Distillation Sampling (SDS) and its variants by directly connecting Consistency Distillation (CD) to score distillation. However, due to the imbalance between…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Jiahao Zhu , Zixuan Chen , Guangcong Wang , Xiaohua Xie , Yi Zhou

Recent innovations on text-to-3D generation have featured Score Distillation Sampling (SDS), which enables the zero-shot learning of implicit 3D models (NeRF) by directly distilling prior knowledge from 2D diffusion models. However, current…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Yang Chen , Yingwei Pan , Haibo Yang , Ting Yao , Tao Mei

Unlike bitmap images, scalable vector graphics (SVG) maintain quality when scaled, frequently employed in computer vision and artistic design in the representation of SVG code. In this era of proliferating AI-powered systems, enabling AI to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Jinke Li , Jiarui Yu , Chenxing Wei , Hande Dong , Qiang Lin , Liangjing Yang , Zhicai Wang , Yanbin Hao

Artificial Intelligence Generated Content (AIGC) has shown remarkable progress in generating realistic images. However, in this paper, we take a step "backward" and address AIGC for the most rudimentary visual modality of human sketches.…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Zhiyu Qu , Tao Xiang , Yi-Zhe Song

With the rising industrial attention to 3D virtual modeling technology, generating novel 3D content based on specified conditions (e.g. text) has become a hot issue. In this paper, we propose a new generative 3D modeling framework called…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Muheng Li , Yueqi Duan , Jie Zhou , Jiwen Lu

Score Distillation Sampling (SDS) enables high-quality text-to-3D generation by supervising 3D models through the denoising of multi-view 2D renderings, using a pretrained text-to-image diffusion model to align with the input prompt and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Weimin Bai , Yubo Li , Weijian Luo , Wenzheng Chen , He Sun

Font design is of vital importance in the digital content design and modern printing industry. Developing algorithms capable of automatically synthesizing vector fonts can significantly facilitate the font design process. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Zeqing Xia , Bojun Xiong , Zhouhui Lian

Recently, with the rapid advancements of generative models, the field of visual text generation has witnessed significant progress. However, it is still challenging to render high-quality text images in real-world scenarios, as three…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Yuanzhi Zhu , Jiawei Liu , Feiyu Gao , Wenyu Liu , Xinggang Wang , Peng Wang , Fei Huang , Cong Yao , Zhibo Yang

Nowadays, there are many diffusion and autoregressive models that show impressive results for generating images from text and other input domains. However, these methods are not intended for ultra-high-resolution image synthesis. Vector…

Computer Vision and Pattern Recognition · Computer Science 2023-06-13 Maria Dziuba , Ivan Jarsky , Valeria Efimova , Andrey Filchenkov

Score Distillation Sampling (SDS) has emerged as a prevalent technique for text-to-3D generation, enabling 3D content creation by distilling view-dependent information from text-to-2D guidance. However, they frequently exhibit shortcomings…

Computer Vision and Pattern Recognition · Computer Science 2024-09-20 Zeyu Cai , Duotun Wang , Yixun Liang , Zhijing Shao , Ying-Cong Chen , Xiaohang Zhan , Zeyu Wang

Storytelling video generation (SVG) aims to produce coherent and visually rich multi-scene videos that follow a structured narrative. Existing methods primarily employ LLM for high-level planning to decompose a story into scene-level…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Zun Wang , Jialu Li , Han Lin , Jaehong Yoon , Mohit Bansal

The emergence of virtual reality has necessitated the generation of detailed and customizable 3D hand models for interaction in the virtual world. However, the current methods for 3D hand model generation are both expensive and cumbersome,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Green Rosh , Prateek Kukreja , Vishakha SR , Pawan Prasad B H