English
Related papers

Related papers: MotionCtrl: A Unified and Flexible Motion Controll…

200 papers

This paper presents a method that allows users to design cinematic video shots in the context of image-to-video generation. Shot design, a critical aspect of filmmaking, involves meticulously planning both camera movements and object…

Computer Vision and Pattern Recognition · Computer Science 2025-02-07 Jinbo Xing , Long Mai , Cusuh Ham , Jiahui Huang , Aniruddha Mahapatra , Chi-Wing Fu , Tien-Tsin Wong , Feng Liu

Human motion generation is essential for fields such as animation, robotics, and virtual reality, requiring models that effectively capture motion dynamics from text descriptions. Existing approaches often rely on Contrastive Language-Image…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Gabriel Maldonado , Armin Danesh Pazho , Ghazal Alinezhad Noghre , Vinit Katariya , Hamed Tabkhi

We propose MotionAgent, enabling fine-grained motion control for text-guided image-to-video generation. The key technique is the motion field agent that converts motion information in text prompts into explicit motion fields, providing…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xinyao Liao , Xianfang Zeng , Liao Wang , Gang Yu , Guosheng Lin , Chi Zhang

Video generation technologies are developing rapidly and have broad potential applications. Among these technologies, camera control is crucial for generating professional-quality videos that accurately meet user expectations. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Wanquan Feng , Jiawei Liu , Pengqi Tu , Tianhao Qi , Mingzhen Sun , Tianxiang Ma , Songtao Zhao , Siyu Zhou , Qian He

Generating videos with realistic and physically plausible motion is one of the main recent challenges in computer vision. While diffusion models are achieving compelling results in image generation, video diffusion models are limited by…

Machine Learning · Computer Science 2024-10-28 Luca Savant Aira , Antonio Montanaro , Emanuele Aiello , Diego Valsesia , Enrico Magli

This paper introduces CameraCtrl II, a framework that enables large-scale dynamic scene exploration through a camera-controlled video diffusion model. Previous camera-conditioned video generative models suffer from diminished video dynamics…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Hao He , Ceyuan Yang , Shanchuan Lin , Yinghao Xu , Meng Wei , Liangke Gui , Qi Zhao , Gordon Wetzstein , Lu Jiang , Hongsheng Li

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

With the rapid development of AI-generated content (AIGC), video generation has emerged as one of its most dynamic and impactful subfields. In particular, the advancement of video generation foundation models has led to growing demand for…

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

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

Zero-shot Text-to-Video synthesis generates videos based on prompts without any videos. Without motion information from videos, motion priors implied in prompts are vital guidance. For example, the prompt "airplane landing on the runway"…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Sitong Su , Litao Guo , Lianli Gao , Hengtao Shen , Jingkuan Song

Recent advancements in language models have demonstrated their adeptness in conducting multi-turn dialogues and retaining conversational context. However, this proficiency remains largely unexplored in other multimodal generative models,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-04 Biao Jiang , Xin Chen , Chi Zhang , Fukun Yin , Zhuoyuan Li , Gang YU , Jiayuan Fan

Controllability, temporal coherence, and detail synthesis remain the most critical challenges in video generation. In this paper, we focus on a commonly used yet underexplored cinematic technique known as Frame In and Frame Out.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Boyang Wang , Xuweiyi Chen , Matheus Gadelha , Zezhou Cheng

Video generation primarily aims to model authentic and customized motion across frames, making understanding and controlling the motion a crucial topic. Most diffusion-based studies on video motion focus on motion customization with…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zeqi Xiao , Yifan Zhou , Shuai Yang , Xingang Pan

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

Recent large-scale pre-trained diffusion models have demonstrated a powerful generative ability to produce high-quality videos from detailed text descriptions. However, exerting control over the motion of objects in videos generated by any…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Changgu Chen , Junwei Shu , Gaoqi He , Changbo Wang , Yang Li

Controlling the movements of dynamic objects and the camera within generated videos is a meaningful yet challenging task. Due to the lack of datasets with comprehensive 6D pose annotations, existing text-to-video methods can not…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Xincheng Shuai , Henghui Ding , Zhenyuan Qin , Hao Luo , Xingjun Ma , Dacheng Tao

Motion-controllable image animation is a fundamental task with a wide range of potential applications. Recent works have made progress in controlling camera or object motion via various motion representations, while they still struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yingjie Chen , Yifang Men , Yuan Yao , Miaomiao Cui , Liefeng Bo

Despite substantial progress in text-to-video generation, achieving precise and flexible control over fine-grained spatiotemporal attributes remains a significant unresolved challenge in video generation research. To address these…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Xu Zhang , Hao Zhou , Haoming Qin , Xiaobin Lu , Jiaxing Yan , Guanzhong Wang , Zeyu Chen , Yi Liu

In this work, we present MotionBooth, an innovative framework designed for animating customized subjects with precise control over both object and camera movements. By leveraging a few images of a specific object, we efficiently fine-tune a…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Jianzong Wu , Xiangtai Li , Yanhong Zeng , Jiangning Zhang , Qianyu Zhou , Yining Li , Yunhai Tong , Kai Chen