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Recent advancements in video generation have been greatly driven by video diffusion models, with camera motion control emerging as a crucial challenge in creating view-customized visual content. This paper introduces trajectory attention, a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zeqi Xiao , Wenqi Ouyang , Yifan Zhou , Shuai Yang , Lei Yang , Jianlou Si , Xingang Pan

We present FlexTraj, a framework for image-to-video generation with flexible point trajectory control. FlexTraj introduces a unified point-based motion representation that encodes each point with a segmentation ID, a temporally consistent…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Zhiyuan Zhang , Can Wang , Dongdong Chen , Jing Liao

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

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

Trajectory-based motion control has emerged as an intuitive and efficient approach for controllable video generation. However, the existing trajectory-based approaches are usually limited to only generating the motion trajectory of the…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Yuhao Li , Mirana Claire Angel , Salman Khan , Yu Zhu , Jinqiu Sun , Yanning Zhang , Fahad Shahbaz Khan

Generative video editing has enabled several intuitive editing operations for short video clips that would previously have been difficult to achieve, especially for non-expert editors. Existing methods focus on prescribing an object's 3D or…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Kiran Chhatre , Hyeonho Jeong , Yulia Gryaditskaya , Christopher E. Peters , Chun-Hao Paul Huang , Paul Guerrero

This paper aims to manipulate multi-entity 3D motions in video generation. Previous methods on controllable video generation primarily leverage 2D control signals to manipulate object motions and have achieved remarkable synthesis results.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Xiao Fu , Xian Liu , Xintao Wang , Sida Peng , Menghan Xia , Xiaoyu Shi , Ziyang Yuan , Pengfei Wan , Di Zhang , Dahua Lin

We study object motion path editing in videos, where the goal is to alter a target object's trajectory while preserving the original scene content. Unlike prior video editing methods that primarily manipulate appearance or rely on…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Quynh Phung , Long Mai , Cusuh Ham , Feng Liu , Jia-Bin Huang , Aniruddha Mahapatra

Motions in a video primarily consist of camera motion, induced by camera movement, and object motion, resulting from object movement. Accurate control of both camera and object motion is essential for video generation. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Zhouxia Wang , Ziyang Yuan , Xintao Wang , Tianshui Chen , Menghan Xia , Ping Luo , Ying Shan

Recent advances in video generation have led to remarkable improvements in visual quality and temporal coherence. Upon this, trajectory-controllable video generation has emerged to enable precise object motion control through explicitly…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Quanhao Li , Zhen Xing , Rui Wang , Hui Zhang , Qi Dai , Zuxuan Wu

Motion control is crucial for generating expressive and compelling video content; however, most existing video generation models rely mainly on text prompts for control, which struggle to capture the nuances of dynamic actions and temporal…

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

Filmmaking and animation production often require sophisticated techniques for coordinating camera transitions and object movements, typically involving labor-intensive real-world capturing. Despite advancements in generative AI for video…

Computer Vision and Pattern Recognition · Computer Science 2024-06-24 Yaowei Li , Xintao Wang , Zhaoyang Zhang , Zhouxia Wang , Ziyang Yuan , Liangbin Xie , Yuexian Zou , Ying Shan

Generating human videos with realistic and controllable motions is a challenging task. While existing methods can generate visually compelling videos, they lack separate control over four key video elements: foreground subject, background…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Jingyun Liang , Jingkai Zhou , Shikai Li , Chenjie Cao , Lei Sun , Yichen Qian , Weihua Chen , Fan Wang

Recent advances in trajectory-controllable video generation have achieved remarkable progress. Previous methods mainly use adapter-based architectures for precise motion control along predefined trajectories. However, all these methods rely…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Quanhao Li , Zhen Xing , Rui Wang , Haidong Cao , Qi Dai , Daoguo Dong , Zuxuan Wu

With the rapid advancement of game and film production, generating interactive motion from texts has garnered significant attention due to its potential to revolutionize content creation processes. In many practical applications, there is a…

Robotics · Computer Science 2025-02-18 Runqi Wang , Caoyuan Ma , Jian Zhao , Hanrui Xu , Dongfang Sun , Haoyang Chen , Lin Xiong , Zheng Wang , Xuelong Li

Camera trajectory generation is a cornerstone in computer graphics, robotics, virtual reality, and cinematography, enabling seamless and adaptive camera movements that enhance visual storytelling and immersive experiences. Despite its…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Zahra Dehghanian , Pouya Ardekhani , Amir Vahedi , Hamid Beigy , Hamid R. Rabiee

Advances in video generation have significantly improved the realism and quality of created scenes. This has fueled interest in developing intuitive tools that let users leverage video generation as world simulators. Text-to-video (T2V)…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Zuhao Liu , Aleksandar Yanev , Ahmad Mahmood , Ivan Nikolov , Saman Motamed , Wei-Shi Zheng , Xi Wang , Lei Sun , Luc Van Gool , Danda Pani Paudel

Recent years have seen substantial progress in diffusion-based controllable video generation. However, achieving precise control in complex scenarios, including fine-grained object parts, sophisticated motion trajectories, and coherent…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Haitao Zhou , Chuang Wang , Rui Nie , Jinlin Liu , Dongdong Yu , Qian Yu , Changhu Wang

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
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