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Related papers: Complet4R: Geometric Complete 4D Reconstruction

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Recent video generators achieve striking photorealism, yet remain fundamentally inconsistent in 3D. We present WorldReel, a 4D video generator that is natively spatio-temporally consistent. WorldReel jointly produces RGB frames together…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shaoheng Fang , Hanwen Jiang , Yunpeng Bai , Niloy J. Mitra , Qixing Huang

Monocular dynamic reconstruction is a challenging and long-standing vision problem due to the highly ill-posed nature of the task. Existing approaches depend on templates, are effective only in quasi-static scenes, or fail to model 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Qianqian Wang , Vickie Ye , Hang Gao , Weijia Zeng , Jake Austin , Zhengqi Li , Angjoo Kanazawa

Depth completion is crucial for many robotic tasks such as autonomous driving, 3-D reconstruction, and manipulation. Despite the significant progress, existing methods remain computationally intensive and often fail to meet the real-time…

Computer Vision and Pattern Recognition · Computer Science 2023-08-01 Tianan Li , Zhehan Chen , Huan Liu , Chen Wang

We present a novel approach for the reconstruction of dynamic geometric shapes using a single hand-held consumer-grade RGB-D sensor at real-time rates. Our method does not require a pre-defined shape template to start with and builds up the…

Computer Vision and Pattern Recognition · Computer Science 2016-08-02 Matthias Innmann , Michael Zollhöfer , Matthias Nießner , Christian Theobalt , Marc Stamminger

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

3D shape completion has broad applications in robotics, digital twin reconstruction, and extended reality (XR). Although recent advances in 3D object and scene completion have achieved impressive results, existing methods lack 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Bardienus P. Duisterhof , Jan Oberst , Bowen Wen , Stan Birchfield , Deva Ramanan , Jeffrey Ichnowski

Recent advancements in diffusion models for 2D and 3D content creation have sparked a surge of interest in generating 4D content. However, the scarcity of 3D scene datasets constrains current methodologies to primarily object-centric…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Dejia Xu , Hanwen Liang , Neel P. Bhatt , Hezhen Hu , Hanxue Liang , Konstantinos N. Plataniotis , Zhangyang Wang

Reference-driven image completion, which restores missing regions in a target view using additional images, is particularly challenging when the target view differs significantly from the references. Existing generative methods rely solely…

Computer Vision and Pattern Recognition · Computer Science 2025-10-06 Beibei Lin , Tingting Chen , Robby T. Tan

4D head capture aims to generate dynamic topological meshes and corresponding texture maps from videos, which is widely utilized in movies and games for its ability to simulate facial muscle movements and recover dynamic textures in…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Xuanchen Li , Yuhao Cheng , Xingyu Ren , Haozhe Jia , Di Xu , Wenhan Zhu , Yichao Yan

Understanding and predicting dynamics of the physical world can enhance a robot's ability to plan and interact effectively in complex environments. While recent video generation models have shown strong potential in modeling dynamic scenes,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Zeyi Liu , Shuang Li , Eric Cousineau , Siyuan Feng , Benjamin Burchfiel , Shuran Song

Video-conditioned 4D shape generation aims to recover time-varying 3D geometry and view-consistent appearance directly from an input video. In this work, we introduce a native video-to-4D shape generation framework that synthesizes a single…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Jiraphon Yenphraphai , Ashkan Mirzaei , Jianqi Chen , Jiaxu Zou , Sergey Tulyakov , Raymond A. Yeh , Peter Wonka , Chaoyang Wang

Recent advances in vision foundation models have revolutionized geometry reconstruction and semantic understanding. Yet, most of the existing approaches treat these capabilities in isolation, leading to redundant pipelines and compounded…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Chaoyi Zhou , Run Wang , Feng Luo , Mert D. Pesé , Zhiwen Fan , Yiqi Zhong , Siyu Huang

In recent years, 3D visual foundation models pioneered by pointmap-based approaches such as DUSt3R have attracted a lot of interest, achieving impressive accuracy and strong generalization across diverse scenes. However, these methods are…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Shuang Guo , Filbert Febryanto , Lei Sun , Guillermo Gallego

High-quality 4D reconstruction enables photorealistic and immersive rendering of the dynamic real world. However, unlike static scenes that can be fully captured with a single camera, high-quality dynamic scenes typically require dense…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Weihong Pan , Xiaoyu Zhang , Zhuang Zhang , Zhichao Ye , Nan Wang , Haomin Liu , Guofeng Zhang

We tackle the problem of automatically reconstructing a complete 3D model of a scene from a single RGB image. This challenging task requires inferring the shape of both visible and occluded surfaces. Our approach utilizes viewer-centered,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-28 Daeyun Shin , Zhile Ren , Erik B. Sudderth , Charless C. Fowlkes

Video world models aim to simulate dynamic, real-world environments, yet existing methods struggle to provide unified and precise control over camera and multi-object motion, as videos inherently capture dynamics in the projected 2D image…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Sixiao Zheng , Minghao Yin , Wenbo Hu , Xiaoyu Li , Ying Shan , Yanwei Fu

Multimodal transformer exhibits high capacity and flexibility to align image and text for visual grounding. However, the existing encoder-only grounding framework (e.g., TransVG) suffers from heavy computation due to the self-attention…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Fengyuan Shi , Ruopeng Gao , Weilin Huang , Limin Wang

We present a novel framework named NeuralRecon for real-time 3D scene reconstruction from a monocular video. Unlike previous methods that estimate single-view depth maps separately on each key-frame and fuse them later, we propose to…

Computer Vision and Pattern Recognition · Computer Science 2021-04-02 Jiaming Sun , Yiming Xie , Linghao Chen , Xiaowei Zhou , Hujun Bao

This paper targets high-fidelity and real-time view synthesis of dynamic 3D scenes at 4K resolution. Recently, some methods on dynamic view synthesis have shown impressive rendering quality. However, their speed is still limited when…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Zhen Xu , Sida Peng , Haotong Lin , Guangzhao He , Jiaming Sun , Yujun Shen , Hujun Bao , Xiaowei Zhou

Many robotic tasks involving some form of 3D visual perception greatly benefit from a complete knowledge of the working environment. However, robots often have to tackle unstructured environments and their onboard visual sensors can only…

Computer Vision and Pattern Recognition · Computer Science 2022-10-24 Andrea Rosasco , Stefano Berti , Fabrizio Bottarel , Michele Colledanchise , Lorenzo Natale