English
Related papers

Related papers: 3DreamBooth: High-Fidelity 3D Subject-Driven Video…

200 papers

Most existing video diffusion models (VDMs) are limited to mere text conditions. Thereby, they are usually lacking in control over visual appearance and geometry structure of the generated videos. This work presents Moonshot, a new video…

Computer Vision and Pattern Recognition · Computer Science 2024-01-04 David Junhao Zhang , Dongxu Li , Hung Le , Mike Zheng Shou , Caiming Xiong , Doyen Sahoo

Recent text-to-image generation models like DreamBooth have made remarkable progress in generating highly customized images of a target subject, by fine-tuning an ``expert model'' for a given subject from a few examples. However, this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-03 Wenhu Chen , Hexiang Hu , Yandong Li , Nataniel Ruiz , Xuhui Jia , Ming-Wei Chang , William W. Cohen

Generating articulated objects, such as laptops and microwaves, is a crucial yet challenging task with extensive applications in Embodied AI and AR/VR. Current image-to-3D methods primarily focus on surface geometry and texture, neglecting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Ruijie Lu , Yu Liu , Jiaxiang Tang , Junfeng Ni , Yuxiang Wang , Diwen Wan , Gang Zeng , Yixin Chen , Siyuan Huang

Generating 4D scenes from a single-view video is inherently ill-posed: a single viewpoint lacks the information needed to recover a complete, dynamic scene with full coverage. Existing methods are typically limited to monocular videos,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Tingxi Chen , Ke Hao , Yabo Chen , Zhengxue Cheng , Rong Xie , Li Song , Haibin Huang , Chi Zhang , Xuelong Li

Significant progress has been made in text-to-video generation through the use of powerful generative models and large-scale internet data. However, substantial challenges remain in precisely controlling individual concepts within the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Hanxin Zhu , Tianyu He , Anni Tang , Junliang Guo , Zhibo Chen , Jiang Bian

Training generalist robots demands large-scale, diverse manipulation data, yet real-world collection is prohibitively expensive, and existing simulators are often constrained by fixed asset libraries and manual heuristics. To bridge this…

Robotics · Computer Science 2026-03-20 Songjia He , Zixuan Chen , Hongyu Ding , Dian Shao , Jieqi Shi , Chenxu Li , Jing Huo , Yang Gao

3D-aware image synthesis has attracted increasing interest as it models the 3D nature of our real world. However, performing realistic object-level editing of the generated images in the multi-object scenario still remains a challenge.…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Qian Wang , Yiqun Wang , Michael Birsak , Peter Wonka

Recently, the surge of efficient and automated 3D AI-generated content (AIGC) methods has increasingly illuminated the path of transforming human imagination into complex 3D structures. However, the automated generation of 3D content is…

Graphics · Computer Science 2024-12-20 Pei Chen , Fudong Wang , Yixuan Tong , Jingdong Chen , Ming Yang , Minghui Yang

Recent advancements in generative models have provided promising solutions for synthesizing realistic driving videos, which are crucial for training autonomous driving perception models. However, existing approaches often struggle with…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Wei Wu , Xi Guo , Weixuan Tang , Tingxuan Huang , Chiyu Wang , Dongyue Chen , Chenjing Ding

Recent advances in video generation have shown promise for generating future scenarios, critical for planning and control in autonomous driving and embodied intelligence. However, real-world applications demand more than visually plausible…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Tianshuo Xu , Zhifei Chen , Leyi Wu , Hao Lu , Yuying Chen , Lihui Jiang , Bingbing Liu , Yingcong Chen

A recent frontier in computer vision has been the task of 3D video generation, which consists of generating a time-varying 3D representation of a scene. To generate dynamic 3D scenes, current methods explicitly model 3D temporal dynamics by…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Rishab Parthasarathy , Zachary Ankner , Aaron Gokaslan

Multi-object tracking (MOT) has profound applications in a variety of fields, including surveillance, sports analytics, self-driving, and cooperative robotics. Despite considerable advancements, existing MOT methodologies tend to falter…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Hamza Mukhtar , Muhammad Usman Ghani Khan

In this paper, we study video synthesis with emphasis on simplifying the generation conditions. Most existing video synthesis models or datasets are designed to address complex motions of a single object, lacking the ability of…

Computer Vision and Pattern Recognition · Computer Science 2023-05-24 Yang Wu , Zhibin Liu , Hefeng Wu , Liang Lin

Generating and editing dynamic 3D head avatars are crucial tasks in virtual reality and film production. However, existing methods often suffer from facial distortions, inaccurate head movements, and limited fine-grained editing…

Graphics · Computer Science 2024-11-26 Yangyang Qian , Yuan Sun , Yu Guo

Recent research in subject-driven generation increasingly emphasizes the importance of selective subject features. Nevertheless, accurately selecting the content in a given reference image still poses challenges, especially when selecting…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Junjie Hu , Shuyong Gao , Lingyi Hong , Qishan Wang , Yuzhou Zhao , Yan Wang , Wenqiang Zhang

The creation of 3D human face avatars from a single unconstrained image is a fundamental task that underlies numerous real-world vision and graphics applications. Despite the significant progress made in generative models, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Wenqing Wang , Haosen Yang , Josef Kittler , Xiatian Zhu

Recently, multi-view diffusion-based 3D generation methods have gained significant attention. However, these methods often suffer from shape and texture misalignment across generated multi-view images, leading to low-quality 3D generation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Zhuojiang Cai , Yiheng Zhang , Meitong Guo , Mingdao Wang , Yuwang Wang

The field of generative AI has a transformative impact on various areas, including virtual reality, autonomous driving, the metaverse, gaming, and robotics. Among these applications, 3D object generation techniques are of utmost importance.…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Qinghong Sun , Yangguang Li , ZeXiang Liu , Xiaoshui Huang , Fenggang Liu , Xihui Liu , Wanli Ouyang , Jing Shao

The growing interest in embodied intelligence has brought ego-centric perspectives to contemporary research. One significant challenge within this realm is the accurate localization and tracking of objects in ego-centric videos, primarily…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Shengyu Hao , Wenhao Chai , Zhonghan Zhao , Meiqi Sun , Wendi Hu , Jieyang Zhou , Yixian Zhao , Qi Li , Yizhou Wang , Xi Li , Gaoang Wang

Despite recent advancements in neural 3D reconstruction, the dependence on dense multi-view captures restricts their broader applicability. In this work, we propose \textbf{ViewCrafter}, a novel method for synthesizing high-fidelity novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Wangbo Yu , Jinbo Xing , Li Yuan , Wenbo Hu , Xiaoyu Li , Zhipeng Huang , Xiangjun Gao , Tien-Tsin Wong , Ying Shan , Yonghong Tian