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Related papers: Controllable Video Generation: A Survey

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Recent remarkable advances in large-scale text-to-image diffusion models have inspired a significant breakthrough in text-to-3D generation, pursuing 3D content creation solely from a given text prompt. However, existing text-to-3D…

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

The field of video generation has expanded significantly in recent years, with controllable and compositional video generation garnering considerable interest. Most methods rely on leveraging annotations such as text, objects' bounding…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Aram Davtyan , Sepehr Sameni , Björn Ommer , Paolo Favaro

Talking head generation is to generate video based on a given source identity and target motion. However, current methods face several challenges that limit the quality and controllability of the generated videos. First, the generated face…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Yue Gao , Yuan Zhou , Jinglu Wang , Xiao Li , Xiang Ming , Yan Lu

Video generation models have emerged as high-fidelity models of the physical world, capable of synthesizing high-quality videos capturing fine-grained interactions between agents and their environments conditioned on multi-modal user…

Current motion-controlled image-to-video generation models rigidly follow user-provided trajectories that are often sparse, imprecise, and causally incomplete. Such reliance often yields unnatural or implausible outcomes, especially by…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Lee Hsin-Ying , Hanwen Jiang , Yiqun Mei , Jing Shi , Ming-Hsuan Yang , Zhixin Shu

Text-to-video generation has advanced rapidly in visual fidelity, whereas standard methods still have limited ability to control the subject composition of generated scenes. Prior work shows that adding localized text control signals, such…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Guofeng Zhang , Angtian Wang , Jacob Zhiyuan Fang , Liming Jiang , Haotian Yang , Bo Liu , Yiding Yang , Guang Chen , Longyin Wen , Alan Yuille , Chongyang Ma

We introduce layered controllable video generation, where we, without any supervision, decompose the initial frame of a video into foreground and background layers, with which the user can control the video generation process by simply…

Computer Vision and Pattern Recognition · Computer Science 2022-10-05 Jiahui Huang , Yuhe Jin , Kwang Moo Yi , Leonid Sigal

In recent years, significant progress has been made in the development of text-to-image generation models. However, these models still face limitations when it comes to achieving full controllability during the generation process. Often,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Salaheldin Mohamed

Recent diffusion models achieve strong photorealism and fluency in video generation, yet remain fragile under abstract, sparse or complex conditions, leading to poor performance in professional production workflows such as storyboard…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Hongji Yang , Songlian Li , Yucheng Zhou , Xiaotong Zhao , Alan Zhao , Chengzhong Xu , Jianbing Shen

Controllable Text Generation (CTG) is emerging area in the field of natural language generation (NLG). It is regarded as crucial for the development of advanced text generation technologies that better meet the specific constraints in…

Computation and Language · Computer Science 2023-08-25 Hanqing Zhang , Haolin Song , Shaoyu Li , Ming Zhou , Dawei Song

While most research on controllable text generation has focused on steering base Language Models, the emerging instruction-tuning and prompting paradigm offers an alternate approach to controllability. We compile and release ConGenBench, a…

Computation and Language · Computer Science 2024-05-03 Dhananjay Ashok , Barnabas Poczos

Diffusion generative models have recently become a powerful technique for creating and modifying high-quality, coherent video content. This survey provides a comprehensive overview of the critical components of diffusion models for video…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Andrew Melnik , Michal Ljubljanac , Cong Lu , Qi Yan , Weiming Ren , Helge Ritter

Text-guided generative diffusion models unlock powerful image creation and editing tools. While these have been extended to video generation, current approaches that edit the content of existing footage while retaining structure require…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Patrick Esser , Johnathan Chiu , Parmida Atighehchian , Jonathan Granskog , Anastasis Germanidis

Recently, ChatGPT, along with DALL-E-2 and Codex,has been gaining significant attention from society. As a result, many individuals have become interested in related resources and are seeking to uncover the background and secrets behind its…

Artificial Intelligence · Computer Science 2023-03-09 Yihan Cao , Siyu Li , Yixin Liu , Zhiling Yan , Yutong Dai , Philip S. Yu , Lichao Sun

Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While text is convenient…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Jinbo Xing , Menghan Xia , Yuxin Liu , Yuechen Zhang , Yong Zhang , Yingqing He , Hanyuan Liu , Haoxin Chen , Xiaodong Cun , Xintao Wang , Ying Shan , Tien-Tsin Wong

The open-domain video generation models are constrained by the scale of the training video datasets, and some less common actions still cannot be generated. Some researchers explore video editing methods and achieve action generation by…

Computer Vision and Pattern Recognition · Computer Science 2024-08-26 Jianzhi Liu , Junchen Zhu , Lianli Gao , Heng Tao Shen , Jingkuan Song

The growing capabilities of AI in generating video content have brought forward significant challenges in effectively evaluating these videos. Unlike static images or text, video content involves complex spatial and temporal dynamics which…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Xiao Liu , Xinhao Xiang , Zizhong Li , Yongheng Wang , Zhuoheng Li , Zhuosheng Liu , Weidi Zhang , Weiqi Ye , Jiawei Zhang

We tackle the long video generation problem, i.e.~generating videos beyond the output length of video generation models. Due to the computation resource constraints, video generation models can only generate video clips that are relatively…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Hsin-Ping Huang , Yu-Chuan Su , Ming-Hsuan Yang

Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Zhengfei Kuang , Shengqu Cai , Hao He , Yinghao Xu , Hongsheng Li , Leonidas Guibas , Gordon Wetzstein

Music enhances video narratives and emotions, driving demand for automatic video-to-music (V2M) generation. However, existing V2M methods relying solely on visual features or supplementary textual inputs generate music in a black-box…

Multimedia · Computer Science 2025-07-29 Junxian Wu , Weitao You , Heda Zuo , Dengming Zhang , Pei Chen , Lingyun Sun