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Related papers: Seeing World Dynamics in a Nutshell

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In this paper, we propose NeoVerse, a versatile 4D world model that is capable of 4D reconstruction, novel-trajectory video generation, and rich downstream applications. We first identify a common limitation of scalability in current 4D…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Yuxue Yang , Lue Fan , Ziqi Shi , Junran Peng , Feng Wang , Zhaoxiang Zhang

Novel-view synthesis aims to generate novel views of a scene from multiple input images or videos, and recent advancements like 3D Gaussian splatting (3DGS) have achieved notable success in producing photorealistic renderings with efficient…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Xi Liu , Chaoyi Zhou , Siyu Huang

Producing long, coherent video sequences with stable 3D structure remains a major challenge, particularly in streaming scenarios. Motivated by this, we introduce Endless World, a real-time framework for infinite, 3D-consistent video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Ke Zhang , Yiqun Mei , Jiacong Xu , Vishal M. Patel

Video tokenization procedure is critical for a wide range of video processing tasks. Most existing approaches directly transform video into fixed-grid and patch-wise tokens, which exhibit limited versatility. Spatially, uniformly allocating…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Zhenghao Chen , Zicong Chen , Lei Liu , Yiming Wu , Dong Xu

We present Orientation-anchored Gaussian Splatting (OriGS), a novel framework for high-quality 4D reconstruction from casually captured monocular videos. While recent advances extend 3D Gaussian Splatting to dynamic scenes via various…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Junyi Wu , Jiachen Tao , Haoxuan Wang , Gaowen Liu , Ramana Rao Kompella , Yan Yan

Dynamic 3D point cloud sequences serve as one of the most common and practical representation modalities of dynamic real-world environments. However, their unstructured nature in both spatial and temporal domains poses significant…

Computer Vision and Pattern Recognition · Computer Science 2024-06-24 Yiming Zeng , Junhui Hou , Qijian Zhang , Siyu Ren , Wenping Wang

The accurate reconstruction of dynamic street scenes is critical for applications in autonomous driving, augmented reality, and virtual reality. Traditional methods relying on dense point clouds and triangular meshes struggle with moving…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Peizhen Zheng , Dongjing Jiang , Qingchong Jiao , Redouane EL Bouchtaoui , Flynnwell Jianfei Zhang

World models aim to endow AI systems with the ability to represent, generate, and interact with dynamic environments in a coherent and temporally consistent manner. While recent video generation models have demonstrated impressive visual…

Reconstructing clean, distractor-free 3D scenes from real-world captures remains a significant challenge, particularly in highly dynamic and cluttered settings such as egocentric videos. To tackle this problem, we introduce DeGauss, a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Rui Wang , Quentin Lohmeyer , Mirko Meboldt , Siyu Tang

In this paper, we aim to model 3D scene geometry, appearance, and physical information just from dynamic multi-view videos in the absence of any human labels. By leveraging physics-informed losses as soft constraints or integrating simple…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Jinxi Li , Ziyang Song , Bo Yang

Recent advancements in static feed-forward scene reconstruction have demonstrated significant progress in high-quality novel view synthesis. However, these models often struggle with generalizability across diverse environments and fail to…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Hanxue Liang , Jiawei Ren , Ashkan Mirzaei , Antonio Torralba , Ziwei Liu , Igor Gilitschenski , Sanja Fidler , Cengiz Oztireli , Huan Ling , Zan Gojcic , Jiahui Huang

Recent advances in neural rendering have improved both training and rendering times by orders of magnitude. While these methods demonstrate state-of-the-art quality and speed, they are designed for photogrammetry of static scenes and do not…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Muhammed Kocabas , Jen-Hao Rick Chang , James Gabriel , Oncel Tuzel , Anurag Ranjan

World generation is a fundamental capability for applications like video games, simulation, and robotics. However, existing approaches face three main obstacles: controllability, scalability, and efficiency. End-to-end scene generation…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Han-Hung Lee , Cheng-Yu Yang , Yu-Lun Liu , Angel X. Chang

In this paper, we present a novel method that facilitates the creation of vivid 3D Gaussian avatars from monocular video inputs (GVA). Our innovation lies in addressing the intricate challenges of delivering high-fidelity human body…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Xinqi Liu , Chenming Wu , Jialun Liu , Xing Liu , Jinbo Wu , Chen Zhao , Haocheng Feng , Errui Ding , Jingdong Wang

We introduce GoMAvatar, a novel approach for real-time, memory-efficient, high-quality animatable human modeling. GoMAvatar takes as input a single monocular video to create a digital avatar capable of re-articulation in new poses and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Jing Wen , Xiaoming Zhao , Zhongzheng Ren , Alexander G. Schwing , Shenlong Wang

Reconstructing high-fidelity animatable human avatars from monocular videos remains challenging due to insufficient geometric information in single-view observations. While recent 3D Gaussian Splatting methods have shown promise, they…

Computer Vision and Pattern Recognition · Computer Science 2025-09-19 Jinlong Fan , Bingyu Hu , Xingguang Li , Yuxiang Yang , Jing Zhang

2D Gaussian Splatting (2DGS) has recently become a promising paradigm for high-quality video representation. However, existing methods employ content-agnostic or spatio-temporal feature overlapping embeddings to predict canonical Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Jierun Lin , Jiacong Chen , Qingyu Mao , Shuai Liu , Xiandong Meng , Fanyang Meng , Yongsheng Liang

Dynamic reconstruction and spatiotemporal novel-view synthesis of non-rigidly deforming scenes recently gained increased attention. While existing work achieves impressive quality and performance on multi-view or teleporting camera setups,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Moritz Kappel , Florian Hahlbohm , Timon Scholz , Susana Castillo , Christian Theobalt , Martin Eisemann , Vladislav Golyanik , Marcus Magnor

We introduce LivingWorld, an interactive framework for generating 4D worlds with environmental dynamics from a single image. While recent advances in 3D scene generation enable large-scale environment creation, most approaches focus…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Hyeongju Mun , In-Hwan Jin , Sohyeong Kim , Kyeongbo Kong

We present Gaussian See, Gaussian Do, a novel approach for semantic 3D motion transfer from multiview video. Our method enables rig-free, cross-category motion transfer between objects with semantically meaningful correspondence. Building…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Yarin Bekor , Gal Michael Harari , Or Perel , Or Litany