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Related papers: Full-4D: Generating Full-Scope 4D Scenes from a Si…

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Existing 4D synthesis methods primarily focus on object-level generation or dynamic scene synthesis with limited novel views, restricting their ability to generate multi-view consistent and immersive dynamic 4D scenes. To address these…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Junwei Zhou , Xueting Li , Lu Qi , Ming-Hsuan Yang

Traditionally, 3D scene synthesis requires expert knowledge and significant manual effort. Automating this process could greatly benefit fields such as architectural design, robotics simulation, virtual reality, and gaming. Recent…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Rui Huang , Guangyao Zhai , Zuria Bauer , Marc Pollefeys , Federico Tombari , Leonidas Guibas , Gao Huang , Francis Engelmann

In this paper, we propose a novel learning approach for feed-forward one-shot 4D head avatar synthesis. Different from existing methods that often learn from reconstructing monocular videos guided by 3DMM, we employ pseudo multi-view videos…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Yu Deng , Duomin Wang , Baoyuan Wang

We explore the task of embodied view synthesis from monocular videos of deformable scenes. Given a minute-long RGBD video of people interacting with their pets, we render the scene from novel camera trajectories derived from the in-scene…

Computer Vision and Pattern Recognition · Computer Science 2023-10-03 Chonghyuk Song , Gengshan Yang , Kangle Deng , Jun-Yan Zhu , Deva Ramanan

High resolution panoramic video content is paramount for immersive experiences in Virtual Reality, but is non-trivial to collect as it requires specialized equipment and intricate camera setups. In this work, we introduce VideoPanda, a…

We introduce a novel geometry-guided online video view synthesis method with enhanced view and temporal consistency. Traditional approaches achieve high-quality synthesis from dense multi-view camera setups but require significant…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Hyunho Ha , Lei Xiao , Christian Richardt , Thu Nguyen-Phuoc , Changil Kim , Min H. Kim , Douglas Lanman , Numair Khan

Volumetric (4D) performance capture is fundamental for AR/VR content generation. Whereas previous work in 4D performance capture has shown impressive results in studio settings, the technology is still far from being accessible to a typical…

In recent years there have been remarkable breakthroughs in image-to-video generation. However, the 3D consistency and camera controllability of generated frames have remained unsolved. Recent studies have attempted to incorporate camera…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Dejia Xu , Yifan Jiang , Chen Huang , Liangchen Song , Thorsten Gernoth , Liangliang Cao , Zhangyang Wang , Hao Tang

With the rapid advancements in diffusion models and 3D generation techniques, dynamic 3D content generation has become a crucial research area. However, achieving high-fidelity 4D (dynamic 3D) generation with strong spatial-temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Jinwei Li , Huan-ang Gao , Wenyi Li , Haohan Chi , Chenyu Liu , Chenxi Du , Yiqian Liu , Mingju Gao , Guiyu Zhang , Zongzheng Zhang , Li Yi , Yao Yao , Jingwei Zhao , Hongyang Li , Yikai Wang , Hao Zhao

Generating flexible-view 3D scenes, including 360{\deg} rotation and zooming, from single images is challenging due to a lack of 3D data. To this end, we introduce FlexWorld, a novel framework consisting of two key components: (1) a strong…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Luxi Chen , Zihan Zhou , Min Zhao , Yikai Wang , Ge Zhang , Wenhao Huang , Hao Sun , Ji-Rong Wen , Chongxuan Li

Recently, the generation of dynamic 3D objects from a video has shown impressive results. Existing methods directly optimize Gaussians using whole information in frames. However, when dynamic regions are interwoven with static regions…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Liying Yang , Chen Liu , Zhenwei Zhu , Ajian Liu , Hui Ma , Jian Nong , Yanyan Liang

We present WonderZoom, a novel approach to generating 3D scenes with contents across multiple spatial scales from a single image. Existing 3D world generation models remain limited to single-scale synthesis and cannot produce coherent scene…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Jin Cao , Hong-Xing Yu , Jiajun Wu

Generative models have gained significant attention in novel view synthesis (NVS) by alleviating the reliance on dense multi-view captures. However, existing methods typically fall into a conventional paradigm, where generative models first…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Weiliang Chen , Jiayi Bi , Yuanhui Huang , Wenzhao Zheng , Yueqi Duan

Generating dynamic 4D objects from sparse inputs is difficult because it demands joint preservation of appearance and motion coherence across views and time while suppressing artifacts and temporal drift. We hypothesize that the view…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Su Sun , Cheng Zhao , Himangi Mittal , Gaurav Mittal , Rohith Kukkala , Yingjie Victor Chen , Mei Chen

Generating multi-view videos for autonomous driving training has recently gained much attention, with the challenge of addressing both cross-view and cross-frame consistency. Existing methods typically apply decoupled attention mechanisms…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Hannan Lu , Xiaohe Wu , Shudong Wang , Xiameng Qin , Xinyu Zhang , Junyu Han , Wangmeng Zuo , Ji Tao

We introduce Geo4D, a method to repurpose video diffusion models for monocular 3D reconstruction of dynamic scenes. By leveraging the strong dynamic priors captured by large-scale pre-trained video models, Geo4D can be trained using only…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Zeren Jiang , Chuanxia Zheng , Iro Laina , Diane Larlus , Andrea Vedaldi

In this paper, we propose Scene Splatter, a momentum-based paradigm for video diffusion to generate generic scenes from single image. Existing methods, which employ video generation models to synthesize novel views, suffer from limited…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Shengjun Zhang , Jinzhao Li , Xin Fei , Hao Liu , Yueqi Duan

Recent years have witnessed remarkable progress in multi-view diffusion models for 3D content creation. However, there remains a significant gap in image quality and prompt-following ability compared to 2D diffusion models. A critical…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Zeyi Sun , Tong Wu , Pan Zhang , Yuhang Zang , Xiaoyi Dong , Yuanjun Xiong , Dahua Lin , Jiaqi Wang

Despite having tremendous progress in image-to-3D generation, existing methods still struggle to produce multi-view consistent images with high-resolution textures in detail, especially in the paradigm of 2D diffusion that lacks 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Haibo Yang , Yang Chen , Yingwei Pan , Ting Yao , Zhineng Chen , Chong-Wah Ngo , Tao Mei

Reconstructing fast-dynamic scenes from multi-view videos is crucial for high-speed motion analysis and realistic 4D reconstruction. However, the majority of 4D capture systems are limited to frame rates below 30 FPS (frames per second),…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Yutian Chen , Shi Guo , Tianshuo Yang , Lihe Ding , Xiuyuan Yu , Jinwei Gu , Tianfan Xue
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