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The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…

Existing video generation models excel at producing photo-realistic videos from text or images, but often lack physical plausibility and 3D controllability. To overcome these limitations, we introduce PhysCtrl, a novel framework for…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Chen Wang , Chuhao Chen , Yiming Huang , Zhiyang Dou , Yuan Liu , Jiatao Gu , Lingjie Liu

Customized text-to-video generation aims to generate text-guided videos with user-given subjects, which has gained increasing attention. However, existing works are primarily limited to single-subject oriented text-to-video generation,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Hong Chen , Xin Wang , Guanning Zeng , Yipeng Zhang , Yuwei Zhou , Feilin Han , Yaofei Wu , Wenwu Zhu

Recent advancements in diffusion models have greatly improved the quality and diversity of synthesized content. To harness the expressive power of diffusion models, researchers have explored various controllable mechanisms that allow users…

Computer Vision and Pattern Recognition · Computer Science 2023-04-28 Tsai-Shien Chen , Chieh Hubert Lin , Hung-Yu Tseng , Tsung-Yi Lin , Ming-Hsuan Yang

Recent advancements in diffusion models have significantly enhanced the data synthesis with 2D control. Yet, precise 3D control in street view generation, crucial for 3D perception tasks, remains elusive. Specifically, utilizing Bird's-Eye…

Computer Vision and Pattern Recognition · Computer Science 2024-05-06 Ruiyuan Gao , Kai Chen , Enze Xie , Lanqing Hong , Zhenguo Li , Dit-Yan Yeung , Qiang Xu

Advancements in diffusion models have significantly improved video quality, directing attention to fine-grained controllability. However, many existing methods depend on fine-tuning large-scale video models for specific tasks, which becomes…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Sangwon Jang , Taekyung Ki , Jaehyeong Jo , Jaehong Yoon , Soo Ye Kim , Zhe Lin , Sung Ju Hwang

Attributes such as style, fine-grained text, and trajectory are specific conditions for describing motion. However, existing methods often lack precise user control over motion attributes and suffer from limited generalizability to unseen…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Mingjie Wei , Xuemei Xie , Guangming Shi

Audio-video (AV) generation has recently made strong progress in perceptual quality and multimodal coherence, yet generating content with plausible motion-sound relations remains challenging. Existing methods often produce object motions…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Junchao Liao , Zhenghao Zhang , Xiangyu Meng , Litao Li , Ziying Zhang , Siyu Zhu , Long Qin , Weizhi Wang

We present DiverseMotion, a new approach for synthesizing high-quality human motions conditioned on textual descriptions while preserving motion diversity.Despite the recent significant process in text-based human motion generation,existing…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Yunhong Lou , Linchao Zhu , Yaxiong Wang , Xiaohan Wang , Yi Yang

Controllable generation of 3D human motions becomes an important topic as the world embraces digital transformation. Existing works, though making promising progress with the advent of diffusion models, heavily rely on meticulously captured…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Nhat M. Hoang , Kehong Gong , Chuan Guo , Michael Bi Mi

Recent advancements in 2D/3D generative techniques have facilitated the generation of dynamic 3D objects from monocular videos. Previous methods mainly rely on the implicit neural radiance fields (NeRF) or explicit Gaussian Splatting as the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Zhiqi Li , Yiming Chen , Peidong Liu

We present I2V3D, a novel framework for animating static images into dynamic videos with precise 3D control, leveraging the strengths of both 3D geometry guidance and advanced generative models. Our approach combines the precision of a…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Zhiyuan Zhang , Dongdong Chen , Jing Liao

Data scarcity continues to be a major challenge in the field of robotic manipulation. Although diffusion models provide a promising solution for generating robotic manipulation videos, existing methods largely depend on 2D trajectories,…

Robotics · Computer Science 2025-11-14 Ying Li , Xiaobao Wei , Xiaowei Chi , Yuming Li , Zhongyu Zhao , Hao Wang , Ningning Ma , Ming Lu , Sirui Han , Shanghang Zhang

Existing text-to-video (T2V) models often struggle with generating videos with sufficiently pronounced or complex actions. A key limitation lies in the text prompt's inability to precisely convey intricate motion details. To address this,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Qiang Zhou , Shaofeng Zhang , Nianzu Yang , Ye Qian , Hao Li

Recent text-to-video diffusion models have achieved impressive progress. In practice, users often desire the ability to control object motion and camera movement independently for customized video creation. However, current methods lack the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Shiyuan Yang , Liang Hou , Haibin Huang , Chongyang Ma , Pengfei Wan , Di Zhang , Xiaodong Chen , Jing Liao

We present a video generation model that accurately reproduces object motion, changes in camera viewpoint, and new content that arises over time. Existing video generation methods often fail to produce new content as a function of time…

Computer Vision and Pattern Recognition · Computer Science 2022-06-10 Tim Brooks , Janne Hellsten , Miika Aittala , Ting-Chun Wang , Timo Aila , Jaakko Lehtinen , Ming-Yu Liu , Alexei A. Efros , Tero Karras

Surgical video generation can enhance medical education and research, but existing methods lack fine-grained motion control and realism. We introduce SurgSora, a framework that generates high-fidelity, motion-controllable surgical videos…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Tong Chen , Shuya Yang , Junyi Wang , Long Bai , Hongliang Ren , Luping Zhou

Explorable 3D world generation from a single image or text prompt forms a cornerstone of spatial intelligence. Recent works utilize video model to achieve wide-scope and generalizable 3D world generation. However, existing approaches often…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Zhongqi Yang , Wenhang Ge , Yuqi Li , Jiaqi Chen , Haoyuan Li , Mengyin An , Fei Kang , Hua Xue , Baixin Xu , Yuyang Yin , Eric Li , Yang Liu , Yikai Wang , Hao-Xiang Guo , Yahui Zhou

Simple as it seems, moving an object to another location within an image is, in fact, a challenging image-editing task that requires re-harmonizing the lighting, adjusting the pose based on perspective, accurately filling occluded regions,…

Graphics · Computer Science 2025-03-12 Xin Yu , Tianyu Wang , Soo Ye Kim , Paul Guerrero , Xi Chen , Qing Liu , Zhe Lin , Xiaojuan Qi

Recent advancements in personalized Text-to-Video (T2V) generation have made significant strides in synthesizing character-specific content. However, these methods face a critical limitation: the inability to perform fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Haopeng Fang , Di Qiu , Binjie Mao , He Tang
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