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Related papers: Setting the Stage: Text-Driven Scene-Consistent Im…

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Recent text-to-image models have revolutionized image generation, but they still struggle with maintaining concept consistency across generated images. While existing works focus on character consistency, they often overlook the crucial…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Quanjian Song , Donghao Zhou , Jingyu Lin , Fei Shen , Jiaze Wang , Xiaowei Hu , Cunjian Chen , Pheng-Ann Heng

Recent text-to-image generation methods provide a simple yet exciting conversion capability between text and image domains. While these methods have incrementally improved the generated image fidelity and text relevancy, several pivotal…

Computer Vision and Pattern Recognition · Computer Science 2022-03-25 Oran Gafni , Adam Polyak , Oron Ashual , Shelly Sheynin , Devi Parikh , Yaniv Taigman

Advancements in generative models have sparked significant interest in generating images while adhering to specific structural guidelines. Scene graph to image generation is one such task of generating images which are consistent with the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Rameshwar Mishra , A V Subramanyam

We present CineVerse, a novel framework for the task of cinematic scene composition. Similar to traditional multi-shot generation, our task emphasizes the need for consistency and continuity across frames. However, our task also focuses on…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Quynh Phung , Long Mai , Fabian David Caba Heilbron , Feng Liu , Jia-Bin Huang , Cusuh Ham

We present a method for text-driven perpetual view generation -- synthesizing long-term videos of various scenes solely, given an input text prompt describing the scene and camera poses. We introduce a novel framework that generates such…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Rafail Fridman , Amit Abecasis , Yoni Kasten , Tali Dekel

Text-to-image models are showcasing the impressive ability to create high-quality and diverse generative images. Nevertheless, the transition from freehand sketches to complex scene images remains challenging using diffusion models. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Tianyu Zhang , Xiaoxuan Xie , Xusheng Du , Haoran Xie

Generating realistic images from scene graphs asks neural networks to be able to reason about object relationships and compositionality. As a relatively new task, how to properly ensure the generated images comply with scene graphs or how…

Computer Vision and Pattern Recognition · Computer Science 2019-01-17 Subarna Tripathi , Anahita Bhiwandiwalla , Alexei Bastidas , Hanlin Tang

We propose a data-driven approach for context-aware person image generation. Specifically, we attempt to generate a person image such that the synthesized instance can blend into a complex scene. In our method, the position, scale, and…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Prasun Roy , Saumik Bhattacharya , Subhankar Ghosh , Umapada Pal , Michael Blumenstein

Style-conditioned scene text generation faces unique challenges in extracting precise text styles from complex backgrounds and maintaining fine-grained style consistency across characters, especially for multilingual scripts. We propose…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Zeyu Chen , Fangmin Zhao , Yan Shu , Yichao Liu , Liu Yu , Yu Zhou

Scene text synthesis involves rendering specified texts onto arbitrary images. Current methods typically formulate this task in an end-to-end manner but lack effective character-level guidance during training. Besides, their text encoders,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yibin Wang , Weizhong Zhang , Honghui Xu , Cheng Jin

While diffusion models have significantly advanced the quality of image generation their capability to accurately and coherently render text within these images remains a substantial challenge. Conventional diffusion-based methods for scene…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Qilong Zhangli , Jindong Jiang , Di Liu , Licheng Yu , Xiaoliang Dai , Ankit Ramchandani , Guan Pang , Dimitris N. Metaxas , Praveen Krishnan

Previous text-to-image synthesis algorithms typically use explicit textual instructions to generate/manipulate images accurately, but they have difficulty adapting to guidance in the form of coarsely matched texts. In this work, we attempt…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Mengyao Cui , Zhe Zhu , Shao-Ping Lu , Yulu Yang

Image generation today can produce somewhat realistic images from text prompts. However, if one asks the generator to synthesize a specific camera setting such as creating different fields of view using a 24mm lens versus a 70mm lens, the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Yu Yuan , Xijun Wang , Yichen Sheng , Prateek Chennuri , Xingguang Zhang , Stanley Chan

Recently, diffusion-based image generation methods are credited for their remarkable text-to-image generation capabilities, while still facing challenges in accurately generating multilingual scene text images. To tackle this problem, we…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Lingjun Zhang , Xinyuan Chen , Yaohui Wang , Yue Lu , Yu Qiao

Recent progress on automatic generation of image captions has shown that it is possible to describe the most salient information conveyed by images with accurate and meaningful sentences. In this paper, we propose an image caption system…

Computer Vision and Pattern Recognition · Computer Science 2015-06-23 Junqi Jin , Kun Fu , Runpeng Cui , Fei Sha , Changshui Zhang

Person image generation is an intriguing yet challenging problem. However, this task becomes even more difficult under constrained situations. In this work, we propose a novel pipeline to generate and insert contextually relevant person…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Prasun Roy , Subhankar Ghosh , Saumik Bhattacharya , Umapada Pal , Michael Blumenstein

Scene text editing aims to modify text content within scene images while maintaining style consistency. Traditional methods achieve this by explicitly disentangling style and content from the source image and then fusing the style with the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Zhengyao Fang , Pengyuan Lyu , Jingjing Wu , Chengquan Zhang , Jun Yu , Guangming Lu , Wenjie Pei

Text-conditioned image generation has made significant progress in recent years with generative adversarial networks and more recently, diffusion models. While diffusion models conditioned on text prompts have produced impressive and…

Computer Vision and Pattern Recognition · Computer Science 2023-05-01 Azade Farshad , Yousef Yeganeh , Yu Chi , Chengzhi Shen , Björn Ommer , Nassir Navab

This study aims to investigate the challenge of insufficient three-dimensional context in synthetic datasets for scene text rendering. Although recent advances in diffusion models and related techniques have improved certain aspects of…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Li-Syun Hsiung , Jun-Kai Tu , Kuan-Wu Chu , Yu-Hsuan Chiu , Yan-Tsung Peng , Sheng-Luen Chung , Gee-Sern Jison Hsu

Designing 3D scenes is traditionally a challenging task that demands both artistic expertise and proficiency with complex software. Recent advances in text-to-3D generation have greatly simplified this process by letting users create scenes…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Zeqi Gu , Yin Cui , Zhaoshuo Li , Fangyin Wei , Yunhao Ge , Jinwei Gu , Ming-Yu Liu , Abe Davis , Yifan Ding
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