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Vector graphics are widely used in digital art and highly favored by designers due to their scalability and layer-wise properties. However, the process of creating and editing vector graphics requires creativity and design expertise, making…

Computer Vision and Pattern Recognition · Computer Science 2024-05-21 Peiying Zhang , Nanxuan Zhao , Jing Liao

Scalable Vector Graphics (SVG) has become the de facto standard for vector graphics in digital design, offering resolution independence and precise control over individual elements. Despite their advantages, creating high-quality SVG…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Ronghuan Wu , Wanchao Su , Jing Liao

Vector graphics are widely used in digital art and valued by designers for their scalability and layer-wise topological properties. However, the creation and editing of vector graphics necessitate creativity and design expertise, leading to…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Peiying Zhang , Nanxuan Zhao , Jing Liao

Visual generation grounded in Visual Foundation Model (VFM) representations offers a highly promising unified pathway for integrating visual understanding, perception, and generation. Despite this potential, training large-scale…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Minglei Shi , Haolin Wang , Borui Zhang , Wenzhao Zheng , Bohan Zeng , Ziyang Yuan , Xiaoshi Wu , Yuanxing Zhang , Huan Yang , Xintao Wang , Pengfei Wan , Kun Gai , Jie Zhou , Jiwen Lu

Text-guided scalable vector graphics (SVG) synthesis has broad applications in icon and sketch generation. However, existing text-to-SVG methods often suffer from limited editability, suboptimal visual quality, and low sample diversity. To…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Ximing Xing , Haitao Zhou , Chuang Wang , Jing Zhang , Dong Xu , Qian Yu

While Text-To-Video (T2V) models have advanced rapidly, they continue to struggle with generating legible and coherent text within videos. In particular, existing models often fail to render correctly even short phrases or words and…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Ziyang Liu , Kevin Valencia , Justin Cui

Text-to-video (T2V) generation technology holds potential to transform multiple domains such as education, marketing, entertainment, and assistive technologies for individuals with visual or reading comprehension challenges, by creating…

Graphics · Computer Science 2025-10-07 Nilay Kumar , Priyansh Bhandari , G. Maragatham

Video generation has increasingly gained interest in both academia and industry. Although commercial tools can generate plausible videos, there is a limited number of open-source models available for researchers and engineers. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Haoxin Chen , Menghan Xia , Yingqing He , Yong Zhang , Xiaodong Cun , Shaoshu Yang , Jinbo Xing , Yaofang Liu , Qifeng Chen , Xintao Wang , Chao Weng , Ying Shan

Diffusion models have shown impressive results in text-to-image synthesis. Using massive datasets of captioned images, diffusion models learn to generate raster images of highly diverse objects and scenes. However, designers frequently use…

Computer Vision and Pattern Recognition · Computer Science 2022-11-22 Ajay Jain , Amber Xie , Pieter Abbeel

Although recent text-to-image (T2I) diffusion models excel at aligning generated images with textual prompts, controlling the visual style of the output remains a challenging task. In this work, we propose Style-Prompting Guidance (SPG), a…

Graphics · Computer Science 2025-08-18 Qian Liang , Zichong Chen , Yang Zhou , Hui Huang

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 struggle with poor structural understanding and error accumulation,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Ximing Xing , Juncheng Hu , Ziteng Xue , Jing Zhang , Buyu Li , Sheng Wang , Dong Xu , Qian Yu

Text-guided image-to-video (I2V) generation aims to generate a coherent video that preserves the identity of the input image and semantically aligns with the input prompt. Existing methods typically augment pretrained text-to-video (T2V)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Xun Guo , Mingwu Zheng , Liang Hou , Yuan Gao , Yufan Deng , Pengfei Wan , Di Zhang , Yufan Liu , Weiming Hu , Zhengjun Zha , Haibin Huang , Chongyang Ma

While large-scale datasets have driven significant progress in Text-to-Video (T2V) generative models, these models remain highly sensitive to input prompts, demonstrating that prompt design is critical to generation quality. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Zillur Rahman , Alex Sheng , Cristian Meo

Text-to-Image (T2I) diffusion models have shown impressive results in generating visually compelling images following user prompts. Building on this, various methods further fine-tune the pre-trained T2I model for specific tasks. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-24 Tsu-Jui Fu , Yusu Qian , Chen Chen , Wenze Hu , Zhe Gan , Yinfei Yang

Vector graphics are essential in design, providing artists with a versatile medium for creating resolution-independent and highly editable visual content. Recent advancements in vision-language and diffusion models have fueled interest in…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Sagi Polaczek , Yuval Alaluf , Elad Richardson , Yael Vinker , Daniel Cohen-Or

Text-to-video (T2V) models have shown remarkable capabilities in generating diverse videos. However, they struggle to produce user-desired stylized videos due to (i) text's inherent clumsiness in expressing specific styles and (ii) the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Gongye Liu , Menghan Xia , Yong Zhang , Haoxin Chen , Jinbo Xing , Yibo Wang , Xintao Wang , Yujiu Yang , Ying Shan

Significant advancements in video diffusion models have brought substantial progress to the field of text-to-video (T2V) synthesis. However, existing T2V synthesis model struggle to accurately generate complex motion dynamics, leading to a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Haoran Cheng , Liang Peng , Linxuan Xia , Yuepeng Hu , Hengjia Li , Qinglin Lu , Xiaofei He , Boxi Wu

Scalable Vector Graphics (SVG) are central to digital design due to their inherent scalability and editability. Despite significant advancements in content generation enabled by Visual Language Models (VLMs), existing text-to-SVG generation…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Feiyu Wang , Jiayuan Yang , Zhiyuan Zhao , Da Zhang , Bingyu Li , Peng Liu , Junyu Gao

Scalable Vector Graphics (SVG) is a code-based representation for 2D visuals. Leveraging recent advances in large language models (LLMs), we study text-to-SVG generation and address two persistent gaps: weak generalization and poor…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Hanqi Chen , Zhongyin Zhao , Ye Chen , Zhujin Liang , Bingbing Ni

Recently, the multimedia community has witnessed the rise of diffusion models trained on large-scale multi-modal data for visual content creation, particularly in the field of text-to-image generation. In this paper, we propose a new task…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Jingwen Chen , Yingwei Pan , Ting Yao , Tao Mei
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