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Reading dense text and locating objects within images are fundamental abilities for Large Vision-Language Models (LVLMs) tasked with advanced jobs. Previous LVLMs, including superior proprietary models like GPT-4o, have struggled to excel…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Ya-Qi Yu , Minghui Liao , Jiwen Zhang , Jihao Wu

Despite recent advances in generative models driving significant progress in text rendering, accurately generating complex text and mathematical formulas remains a formidable challenge. This difficulty primarily stems from the limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Zexuan Yan , Jiarui Jin , Yue Ma , Shijian Wang , Jiahui Hu , Wenxiang Jiao , Yuan Lu , Linfeng Zhang

Artistic Glyph Image Generation (AGIG) differs from current creativity-focused generation models by offering finely controllable deterministic generation. It transfers the style of a reference image to a source while preserving its content.…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Xiongbo Lu , Yaxiong Chen , Shengwu Xiong

Large Vision Language Models have achieved fine-grained object perception, but the limitation of image resolution remains a significant obstacle to surpassing the performance of task-specific experts in complex and dense scenarios. Such…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Yufei Zhan , Shurong Zheng , Yousong Zhu , Hongyin Zhao , Fan Yang , Ming Tang , Jinqiao Wang

Multimodal language models (MLLMs) are increasingly paired with vision tools (e.g., depth, flow, correspondence) to enhance visual reasoning. However, despite access to these tool-generated visual cues, MLLMs often fail to benefit from…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Muhammad Kamran Janjua , Hugo Silva , Di Niu , Bahador Rashidi

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

Text-to-image generative models excel in creating images from text but struggle with ensuring alignment and consistency between outputs and prompts. This paper introduces TextMatch, a novel framework that leverages multimodal optimization…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Yucong Luo , Mingyue Cheng , Jie Ouyang , Xiaoyu Tao , Qi Liu

The advancement of open-source text-to-image (T2I) models has been hindered by the absence of large-scale, reasoning-focused datasets and comprehensive evaluation benchmarks, resulting in a performance gap compared to leading closed-source…

Computer Vision and Pattern Recognition · Computer Science 2025-09-12 Rongyao Fang , Aldrich Yu , Chengqi Duan , Linjiang Huang , Shuai Bai , Yuxuan Cai , Kun Wang , Si Liu , Xihui Liu , Hongsheng Li

Multimodal large language models (MLLMs) represent an evolutionary expansion in the capabilities of traditional large language models, enabling them to tackle challenges that surpass the scope of purely text-based applications. It leverages…

Computation and Language · Computer Science 2025-01-17 Jinlong He , Pengfei Li , Gang Liu , Genrong He , Zhaolin Chen , Shenjun Zhong

We introduce GraphicDesignBench (GDB), the first comprehensive benchmark suite designed specifically to evaluate AI models on the full breadth of professional graphic design tasks. Unlike existing benchmarks that focus on natural-image…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Adrienne Deganutti , Elad Hirsch , Haonan Zhu , Jaejung Seol , Purvanshi Mehta

In this paper, we introduce Flash-VL 2B, a novel approach to optimizing Vision-Language Models (VLMs) for real-time applications, targeting ultra-low latency and high throughput without sacrificing accuracy. Leveraging advanced…

Computer Vision and Pattern Recognition · Computer Science 2025-05-15 Bo Zhang , Shuo Li , Runhe Tian , Yang Yang , Jixin Tang , Jinhao Zhou , Lin Ma

Touch is an important sensing modality for humans, but it has not yet been incorporated into a multimodal generative language model. This is partially due to the difficulty of obtaining natural language labels for tactile data and the…

Computer Vision and Pattern Recognition · Computer Science 2024-02-21 Letian Fu , Gaurav Datta , Huang Huang , William Chung-Ho Panitch , Jaimyn Drake , Joseph Ortiz , Mustafa Mukadam , Mike Lambeta , Roberto Calandra , Ken Goldberg

In recent years, the emergence of models capable of generating images from text has attracted considerable interest, offering the possibility of creating realistic images from text descriptions. Yet these advances have also raised concerns…

Computer Vision and Pattern Recognition · Computer Science 2024-04-04 Mamadou Keita , Wassim Hamidouche , Hassen Bougueffa , Abdenour Hadid , Abdelmalik Taleb-Ahmed

Text logo design heavily relies on the creativity and expertise of professional designers, in which arranging element layouts is one of the most important procedures. However, few attention has been paid to this task which needs to take…

Computer Vision and Pattern Recognition · Computer Science 2022-04-07 Yizhi Wang , Guo Pu , Wenhan Luo , Yexin Wang , Pengfei Xiong , Hongwen Kang , Zhouhui Lian

The integration of visual inputs with large language models (LLMs) has led to remarkable advancements in multi-modal capabilities, giving rise to visual large language models (VLLMs). However, effectively harnessing VLLMs for intricate…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Renjie Pi , Lewei Yao , Jiahui Gao , Jipeng Zhang , Tong Zhang

In image editing tasks, high-quality text editing capabilities can significantly reduce both human and material resource costs. Existing methods, however, face significant limitations in terms of stroke accuracy for complex text and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Zhenyu Yan , Jian Wang , Aoqiang Wang , Yuhan Li , Wenxiang Shang , Ran Lin

Lately, researchers in artificial intelligence have been really interested in how language and vision come together, giving rise to the development of multimodal models that aim to seamlessly integrate textual and visual information.…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Rajat Chawla , Arkajit Datta , Tushar Verma , Adarsh Jha , Anmol Gautam , Ayush Vatsal , Sukrit Chaterjee , Mukunda NS , Ishaan Bhola

Generating font glyphs of consistent style from one or a few reference glyphs, i.e., font completion, is an important task in topographical design. As the problem is more well-defined than general image style transfer tasks, thus it has…

Computer Vision and Pattern Recognition · Computer Science 2021-08-31 Ye Yuan , Wuyang Chen , Zhaowen Wang , Matthew Fisher , Zhifei Zhang , Zhangyang Wang , Hailin Jin

Visual Language Models (VLMs) are now sufficiently advanced to support a broad range of applications, including answering complex visual questions, and are increasingly expected to interact with images in varied ways. To evaluate them,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Ludovic Arnould , Salim Khazem , Hugues Ali Mehenni

Multimodal large language models (MLLMs) are designed to process and integrate information from multiple sources, such as text, speech, images, and videos. Despite its success in language understanding, it is critical to evaluate the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-11 Hao Lu , Xuesong Niu , Jiyao Wang , Yin Wang , Qingyong Hu , Jiaqi Tang , Yuting Zhang , Kaishen Yuan , Bin Huang , Zitong Yu , Dengbo He , Shuiguang Deng , Hao Chen , Yingcong Chen , Shiguang Shan
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