English
Related papers

Related papers: ActCam: Zero-Shot Joint Camera and 3D Motion Contr…

200 papers

We are living in a flourishing era of digital media, where everyone has the potential to become a personal filmmaker. Current research on video generation suggests a promising avenue for controllable film creation in pixel space using…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Weiliang Chen , Fangfu Liu , Diankun Wu , Haowen Sun , Jiwen Lu , Yueqi Duan

Despite tremendous recent progress, generative video models still struggle to capture real-world motion, dynamics, and physics. We show that this limitation arises from the conventional pixel reconstruction objective, which biases models…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Hila Chefer , Uriel Singer , Amit Zohar , Yuval Kirstain , Adam Polyak , Yaniv Taigman , Lior Wolf , Shelly Sheynin

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

We present 3DScenePrompt, a framework that generates the next video chunk from arbitrary-length input while enabling precise camera control and preserving scene consistency. Unlike methods conditioned on a single image or a short clip, we…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 JoungBin Lee , Jaewoo Jung , Jisang Han , Takuya Narihira , Kazumi Fukuda , Junyoung Seo , Sunghwan Hong , Yuki Mitsufuji , Seungryong Kim

We present ZeroComp, an effective zero-shot 3D object compositing approach that does not require paired composite-scene images during training. Our method leverages ControlNet to condition from intrinsic images and combines it with a Stable…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Zitian Zhang , Frédéric Fortier-Chouinard , Mathieu Garon , Anand Bhattad , Jean-François Lalonde

Recent video editing advancements rely on accurate pose sequences to animate subjects. However, these efforts are not suitable for cross-species animation due to pose misalignment between species (for example, the poses of a cat differs…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Yuanfeng Xu , Yuhao Chen , Zhongzhan Huang , Zijian He , Guangrun Wang , Philip Torr , Liang Lin

Zero-shot customized video generation has gained significant attention due to its substantial application potential. Existing methods rely on additional models to extract and inject reference subject features, assuming that the Video…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Tao Wu , Yong Zhang , Xiaodong Cun , Zhongang Qi , Junfu Pu , Huanzhang Dou , Guangcong Zheng , Ying Shan , Xi Li

Text-conditioned motion synthesis has made remarkable progress with the emergence of diffusion models. However, the majority of these motion diffusion models are primarily designed for a single character and overlook multi-human…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Zhenzhi Wang , Jingbo Wang , Yixuan Li , Dahua Lin , Bo Dai

The emergence of diffusion models has greatly propelled the progress in image and video generation. Recently, some efforts have been made in controllable video generation, including text-to-video generation and video motion control, among…

Computer Vision and Pattern Recognition · Computer Science 2024-05-02 Teng Hu , Jiangning Zhang , Ran Yi , Yating Wang , Hongrui Huang , Jieyu Weng , Yabiao Wang , Lizhuang Ma

Generating text-editable and pose-controllable character videos have an imperious demand in creating various digital human. Nevertheless, this task has been restricted by the absence of a comprehensive dataset featuring paired video-pose…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 Yue Ma , Yingqing He , Xiaodong Cun , Xintao Wang , Siran Chen , Ying Shan , Xiu Li , Qifeng Chen

Diffusion-based video generation techniques have significantly improved zero-shot talking-head avatar generation, enhancing the naturalness of both head motion and facial expressions. However, existing methods suffer from poor…

Graphics · Computer Science 2025-04-24 Lingzhou Mu , Baiji Liu , Ruonan Zhang , Guiming Mo , Jiawei Jin , Kai Zhang , Haozhi Huang

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

Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an essential component for intelligent systems. Recent approaches have improved temporal coherence…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Melonie de Almeida , Daniela Ivanova , Tong Shi , John H. Williamson , Paul Henderson

Controllability plays a crucial role in video generation, as it allows users to create and edit content more precisely. Existing models, however, lack control of camera pose that serves as a cinematic language to express deeper narrative…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Hao He , Yinghao Xu , Yuwei Guo , Gordon Wetzstein , Bo Dai , Hongsheng Li , Ceyuan Yang

Character animation is a transformative field in computer graphics and vision, enabling dynamic and realistic video animations from static images. Despite advancements, maintaining appearance consistency in animations remains a challenge.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Xiaoyu Jin , Zunnan Xu , Mingwen Ou , Wenming Yang

The "one-shot" technique represents a distinct and sophisticated aesthetic in filmmaking. However, its practical realization is often hindered by prohibitive costs and complex real-world constraints. Although emerging video generation…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Jiawei Liu , Junqiao Li , Jiangfan Deng , Gen Li , Siyu Zhou , Zetao Fang , Shanshan Lao , Zengde Deng , Jianing Zhu , Tingting Ma , Jiayi Li , Yunqiu Wang , Qian He , Xinglong Wu

Video fundamentally intertwines two crucial axes: the dynamic content of a scene and the camera motion through which it is observed. However, existing generation models often entangle these factors, limiting independent control. In this…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Yukun Wang , Ruihuang Li , Jiale Tao , Shiyuan Yang , Liyi Chen , Zhantao Yang , Handz , Yulan Guo , Shuai Shao , Qinglin Lu

Recent advancements in camera-trajectory-guided image-to-video generation offer higher precision and better support for complex camera control compared to text-based approaches. However, they also introduce significant usability challenges,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Teng Li , Guangcong Zheng , Rui Jiang , Shuigen Zhan , Tao Wu , Yehao Lu , Yining Lin , Chuanyun Deng , Yepan Xiong , Min Chen , Lin Cheng , Xi Li

Action recognition is a fundamental ability for social species. Yet, its underlying computations are not well understood. Classical psychophysical studies using simplified stimuli have shown that humans can perceive body motion even under…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Prerana Kumar , Martin A. Giese

Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical sets. To address this, we introduce the task of cinematic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Kaiyi Huang , Yukun Huang , Yu Li , Jianhong Bai , Xintao Wang , Zinan Lin , Xuefei Ning , Jiwen Yu , Pengfei Wan , Yu Wang , Xihui Liu