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Camera control, which achieves diverse visual effects by changing camera position and pose, has attracted widespread attention. However, existing methods face challenges such as complex interaction and limited control capabilities. To…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Xiaoda Yang , Jiayang Xu , Kaixuan Luan , Xinyu Zhan , Hongshun Qiu , Shijun Shi , Hao Li , Shuai Yang , Li Zhang , Checheng Yu , Cewu Lu , Lixin Yang

Recent video generation models demonstrate impressive synthesis capabilities but remain limited by single-modality conditioning, constraining their holistic world understanding. This stems from insufficient cross-modal interaction and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Jiehui Huang , Yuechen Zhang , Xu He , Yuan Gao , Zhi Cen , Bin Xia , Yan Zhou , Xin Tao , Pengfei Wan , Jiaya Jia

In this paper, we propose a novel framework for controllable video diffusion, OmniVDiff , aiming to synthesize and comprehend multiple video visual content in a single diffusion model. To achieve this, OmniVDiff treats all video visual…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Dianbing Xi , Jiepeng Wang , Yuanzhi Liang , Xi Qiu , Yuchi Huo , Rui Wang , Chi Zhang , Xuelong Li

Camera control has been actively studied in text or image conditioned video generation tasks. However, altering camera trajectories of a given video remains under-explored, despite its importance in the field of video creation. It is…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Jianhong Bai , Menghan Xia , Xiao Fu , Xintao Wang , Lianrui Mu , Jinwen Cao , Zuozhu Liu , Haoji Hu , Xiang Bai , Pengfei Wan , Di Zhang

Videos convey richer information than images or text, capturing both spatial and temporal dynamics. However, most existing video customization methods rely on reference images or task-specific temporal priors, failing to fully exploit the…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Pengze Zhang , Yanze Wu , Mengtian Li , Xu Bai , Songtao Zhao , Fulong Ye , Chong Mou , Xinghui Li , Zhuowei Chen , Qian He , Mingyuan Gao

By generating plausible and smooth transitions between two image frames, video inbetweening is an essential tool for video editing and long video synthesis. Traditional works lack the capability to generate complex large motions. While…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Maham Tanveer , Yang Zhou , Simon Niklaus , Ali Mahdavi Amiri , Hao Zhang , Krishna Kumar Singh , Nanxuan Zhao

Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthesize only limited observations of a scene, leading to issues…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Yuheng Liu , Xin Lin , Xinke Li , Baihan Yang , Chen Wang , Kalyan Sunkavalli , Yannick Hold-Geoffroy , Hao Tan , Kai Zhang , Xiaohui Xie , Zifan Shi , Yiwei Hu

Incorporating camera intrinsics into video generation models offers a principled way to control not only scene dynamics but also the imaging process that governs visual appearance. Prior work has primarily focused on extrinsic control, such…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Debabrata Mandal , Zhihan Peng , Yujie Wang , Praneeth Chakravarthula

Recent advancements in video diffusion models have shown exceptional abilities in simulating real-world dynamics and maintaining 3D consistency. This progress inspires us to investigate the potential of these models to ensure dynamic…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Jianhong Bai , Menghan Xia , Xintao Wang , Ziyang Yuan , Xiao Fu , Zuozhu Liu , Haoji Hu , Pengfei Wan , Di Zhang

We introduce UniReal, a unified framework designed to address various image generation and editing tasks. Existing solutions often vary by tasks, yet share fundamental principles: preserving consistency between inputs and outputs while…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Xi Chen , Zhifei Zhang , He Zhang , Yuqian Zhou , Soo Ye Kim , Qing Liu , Yijun Li , Jianming Zhang , Nanxuan Zhao , Yilin Wang , Hui Ding , Zhe Lin , Hengshuang Zhao

Camera-controlled video-to-video (V2V) generation enables dynamic viewpoint synthesis from monocular footage, holding immense potential for interactive filmmaking and live broadcasting. However, existing implicit synthesis methods…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Youcan Xu , Jiaxin Shi , Zhen Wang , Wensong Song , Feifei Shao , Chen Liang , Jun Xiao , Long Chen

We present a unified controllable video generation approach AnimateAnything that facilitates precise and consistent video manipulation across various conditions, including camera trajectories, text prompts, and user motion annotations.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Guojun Lei , Chi Wang , Hong Li , Rong Zhang , Yikai Wang , Weiwei Xu

As virtual reality gains popularity, the demand for controllable creation of immersive and dynamic omnidirectional videos (ODVs) is increasing. While previous text-to-ODV generation methods achieve impressive results, they struggle with…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Weiqi Li , Shijie Zhao , Chong Mou , Xuhan Sheng , Zhenyu Zhang , Qian Wang , Junlin Li , Li Zhang , Jian Zhang

Interactive video generation has significant potential for scene simulation and video creation. However, existing methods often struggle with maintaining scene consistency during long video generation under dynamic camera control due to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Xinhang Gao , Junlin Guan , Shuhan Luo , Wenzhuo Li , Guanghuan Tan , Jiacheng Wang

In recent years there have been remarkable breakthroughs in image-to-video generation. However, the 3D consistency and camera controllability of generated frames have remained unsolved. Recent studies have attempted to incorporate camera…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Dejia Xu , Yifan Jiang , Chen Huang , Liangchen Song , Thorsten Gernoth , Liangliang Cao , Zhangyang Wang , Hao Tang

Prior approaches injecting camera control into diffusion models have focused on specific subsets of 4D consistency tasks: novel view synthesis, text-to-video with camera control, image-to-video, amongst others. Therefore, these fragmented…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Xiang Fan , Sharath Girish , Vivek Ramanujan , Chaoyang Wang , Ashkan Mirzaei , Petr Sushko , Aliaksandr Siarohin , Sergey Tulyakov , Ranjay Krishna

Visual effects (VFX) are essential visual enhancements fundamental to modern cinematic production. Although video generation models offer cost-efficient solutions for VFX production, current methods are constrained by per-effect LoRA…

Computer Vision and Pattern Recognition · Computer Science 2025-12-18 Fangyuan Mao , Aiming Hao , Jintao Chen , Dongxia Liu , Xiaokun Feng , Jiashu Zhu , Meiqi Wu , Chubin Chen , Jiahong Wu , Xiangxiang Chu

Notable breakthroughs in unified understanding and generation modeling have led to remarkable advancements in image understanding, reasoning, production and editing, yet current foundational models predominantly focus on processing images,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Zhiyu Tan , Hao Yang , Luozheng Qin , Jia Gong , Mengping Yang , Hao Li

World models based on video generation demonstrate remarkable potential for simulating interactive environments but face persistent difficulties in two key areas: maintaining long-term content consistency when scenes are revisited and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Tianxing Xu , Zixuan Wang , Guangyuan Wang , Li Hu , Zhongyi Zhang , Peng Zhang , Bang Zhang , Song-Hai Zhang

While large-scale diffusion models have revolutionized video synthesis, achieving precise control over both multi-subject identity and multi-granularity motion remains a significant challenge. Recent attempts to bridge this gap often suffer…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Yujie Wei , Xinyu Liu , Shiwei Zhang , Hangjie Yuan , Jinbo Xing , Zhekai Chen , Xiang Wang , Haonan Qiu , Rui Zhao , Yutong Feng , Ruihang Chu , Yingya Zhang , Yike Guo , Xihui Liu , Hongming Shan
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