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Current text-to-image (T2I) generation models achieve promising results, but they fail on the scenarios where the knowledge implied in the text prompt is uncertain. For example, a T2I model released in February would struggle to generate a…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Chuanhao Li , Jianwen Sun , Yukang Feng , Mingliang Zhai , Yifan Chang , Kaipeng Zhang

Data-driven storytelling has gained prominence in journalism and other data reporting fields. However, the process of creating these stories remains challenging, often requiring the integration of effective visualizations with compelling…

Human-Computer Interaction · Computer Science 2025-04-01 Yu Fu , Dennis Bromley , Vidya Setlur

Story visualization is an under-explored task that falls at the intersection of many important research directions in both computer vision and natural language processing. In this task, given a series of natural language captions which…

Computation and Language · Computer Science 2021-05-24 Adyasha Maharana , Darryl Hannan , Mohit Bansal

Text-image-to-video (TI2V) generation is a critical problem for controllable video generation using both semantic and visual conditions. Most existing methods typically add visual conditions to text-to-video (T2V) foundation models by…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Bolin Lai , Sangmin Lee , Xu Cao , Xiang Li , James M. Rehg

Identity-preserving text-to-video (IPT2V) generation, which aims to create high-fidelity videos with consistent human identity, has become crucial for downstream applications. However, current end-to-end frameworks suffer a critical…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Yuji Wang , Moran Li , Xiaobin Hu , Ran Yi , Jiangning Zhang , Han Feng , Weijian Cao , Yabiao Wang , Chengjie Wang , Lizhuang Ma

Customizing text-to-image (T2I) models has seen tremendous progress recently, particularly in areas such as personalization, stylization, and conditional generation. However, expanding this progress to video generation is still in its…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Hila Chefer , Shiran Zada , Roni Paiss , Ariel Ephrat , Omer Tov , Michael Rubinstein , Lior Wolf , Tali Dekel , Tomer Michaeli , Inbar Mosseri

Sequential vision-to-language or visual storytelling has recently been one of the areas of focus in computer vision and language modeling domains. Though existing models generate narratives that read subjectively well, there could be cases…

Computation and Language · Computer Science 2020-01-07 Aditya Surikuchi , Jorma Laaksonen

Video generation is a challenging yet pivotal task in various industries, such as gaming, e-commerce, and advertising. One significant unresolved aspect within T2V is the effective visualization of text within generated videos. Despite the…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Lin Liu , Quande Liu , Shengju Qian , Yuan Zhou , Wengang Zhou , Houqiang Li , Lingxi Xie , Qi Tian

Transfer learning of large-scale Text-to-Image (T2I) models has recently shown impressive potential for Novel View Synthesis (NVS) of diverse objects from a single image. While previous methods typically train large models on multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Yoonwoo Jeong , Jinwoo Lee , Chiheon Kim , Minsu Cho , Doyup Lee

We address the problem of interactive text-to-image (T2I) generation, designing a reinforcement learning (RL) agent which iteratively improves a set of generated images for a user through a sequence of prompt expansions. Using human raters,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Ofir Nabati , Guy Tennenholtz , ChihWei Hsu , Moonkyung Ryu , Deepak Ramachandran , Yinlam Chow , Xiang Li , Craig Boutilier

Generating videos for visual storytelling can be a tedious and complex process that typically requires either live-action filming or graphics animation rendering. To bypass these challenges, our key idea is to utilize the abundance of…

Computer Vision and Pattern Recognition · Computer Science 2023-07-14 Yingqing He , Menghan Xia , Haoxin Chen , Xiaodong Cun , Yuan Gong , Jinbo Xing , Yong Zhang , Xintao Wang , Chao Weng , Ying Shan , Qifeng Chen

Video generation models are revolutionizing content creation, with image-to-video models drawing increasing attention due to their enhanced controllability, visual consistency, and practical applications. However, despite their popularity,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Wenhao Wang , Yi Yang

Recent progress in text-to-image (T2I) models enables high-quality image generation with flexible textual control. To utilize the abundant visual priors in the off-the-shelf T2I models, a series of methods try to invert an image to proper…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Zijie Wu , Chaohui Yu , Zhen Zhu , Fan Wang , Xiang Bai

Text-to-image generation models can create high-quality images from input prompts. However, they struggle to support the consistent generation of identity-preserving requirements for storytelling. Existing approaches to this problem…

Computer Vision and Pattern Recognition · Computer Science 2025-02-06 Tao Liu , Kai Wang , Senmao Li , Joost van de Weijer , Fahad Shahbaz Khan , Shiqi Yang , Yaxing Wang , Jian Yang , Ming-Ming Cheng

Text-to-image (T2I) systems enable rapid generation of high-fidelity imagery but are misaligned with how visual ideas develop. T2I systems generate outputs that make implicit visual decisions on behalf of the user, often introduce…

Human-Computer Interaction · Computer Science 2026-04-16 Zoe De Simone , Angie Boggust , Fredo Durand , Ashia Wilson , Arvind Satyanarayan

Recent generative models have demonstrated impressive capabilities in generating realistic and visually pleasing images grounded on textual prompts. Nevertheless, a significant challenge remains in applying these models for the more…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Xiaoqian Shen , Mohamed Elhoseiny

Traditional visual storytelling is complex, requiring specialized knowledge and substantial resources, yet often constrained by human creativity and creation precision. While Large Language Models (LLMs) enhance visual storytelling, current…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Yuzhou Huang , Yiran Qin , Shunlin Lu , Xintao Wang , Rui Huang , Ying Shan , Ruimao Zhang

Despite the significant advancements in text-to-image (T2I) generative models, users often face a trial-and-error challenge in practical scenarios. This challenge arises from the complexity and uncertainty of tedious steps such as crafting…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Chengyou Jia , Changliang Xia , Zhuohang Dang , Weijia Wu , Hangwei Qian , Minnan Luo

Visual Storytelling is a challenging multimodal task between Vision & Language, where the purpose is to generate a story for a stream of images. Its difficulty lies on the fact that the story should be both grounded to the image sequence…

Computation and Language · Computer Science 2025-08-21 Admitos Passadakis , Yingjin Song , Albert Gatt

We present Story2Board, a training-free framework for expressive storyboard generation from natural language. Existing methods narrowly focus on subject identity, overlooking key aspects of visual storytelling such as spatial composition,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 David Dinkevich , Matan Levy , Omri Avrahami , Dvir Samuel , Dani Lischinski