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3D scene reconstruction under unposed sparse viewpoints is a highly challenging yet practically important problem, especially in outdoor scenes due to complex lighting and scale variation. With extremely limited input views, directly…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Beizhen Zhao , Sicheng Yu , Guanzhi Ding , Yu Hu , Hao Wang

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

We introduce a novel 3D generative method, Generative 3D Reconstruction (G3DR) in ImageNet, capable of generating diverse and high-quality 3D objects from single images, addressing the limitations of existing methods. At the heart of our…

Computer Vision and Pattern Recognition · Computer Science 2024-04-04 Pradyumna Reddy , Ismail Elezi , Jiankang Deng

We introduce 4DGS360, a diffusion-free framework for 360$^{\circ}$ dynamic object reconstruction from casual monocular video. Existing methods often fail to reconstruct consistent 360$^{\circ}$ geometry, as their heavy reliance on 2D-native…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Jae Won Jang , Yeonjin Chang , Wonsik Shin , Juhwan Cho , Nojun Kwak

3D scene generation is a core technology for gaming, film/VFX, and VR/AR. Growing demand for rapid iteration, high-fidelity detail, and accessible content creation has further increased interest in this area. Existing methods broadly follow…

Computer Vision and Pattern Recognition · Computer Science 2026-01-29 Haozhi Zhu , Miaomiao Zhao , Dingyao Liu , Runze Tian , Yan Zhang , Jie Guo , Fenggen Yu

Recent 4D generation methods complete scene-level missing information using generative models and reconstruct the scene into radiance-based representations. However, these pipelines often present geometric inconsistencies in the generated…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Sunwoo Park , Taesung Kwon , Jong Chul Ye

Reconstructing a dynamic target moving over a large area is challenging. Standard approaches for dynamic object reconstruction require dense coverage in both the viewing space and the temporal dimension, typically relying on multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Jun-Jee Chao , Volkan Isler

Recently, 3D Gaussian Splatting has emerged as a prominent research direction owing to its ultrarapid training speed and high-fidelity rendering capabilities. However, the unstructured and irregular nature of Gaussian point clouds poses…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Xiao Ren , Yu Liu , Ning An , Jian Cheng , Xin Qiao , He Kong

Recovering 4D from monocular video, which jointly estimates dynamic geometry and camera poses, is an inevitably challenging problem. While recent pointmap-based 3D reconstruction methods (e.g., DUSt3R) have made great progress in…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Shizun Wang , Zhenxiang Jiang , Xingyi Yang , Xinchao Wang

Novel view synthesis of dynamic scenes is becoming important in various applications, including augmented and virtual reality. We propose a novel 4D Gaussian Splatting (4DGS) algorithm for dynamic scenes from casually recorded monocular…

Computer Vision and Pattern Recognition · Computer Science 2024-11-14 Mijeong Kim , Jongwoo Lim , Bohyung Han

Decompositional reconstruction of 3D scenes, with complete shapes and detailed texture of all objects within, is intriguing for downstream applications but remains challenging, particularly with sparse views as input. Recent approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Junfeng Ni , Yu Liu , Ruijie Lu , Zirui Zhou , Song-Chun Zhu , Yixin Chen , Siyuan Huang

Current 4D generation methods have achieved noteworthy efficacy with the aid of advanced diffusion generative models. However, these methods lack multi-view spatial-temporal modeling and encounter challenges in integrating diverse prior…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Haiyu Zhang , Xinyuan Chen , Yaohui Wang , Xihui Liu , Yunhong Wang , Yu Qiao

3D Gaussian Splatting (3DGS) has garnered significant attention due to its superior scene representation fidelity and real-time rendering performance, especially for dynamic 3D scene reconstruction (\textit{i.e.}, 4D reconstruction).…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Henan Wang , Hanxin Zhu , Xinliang Gong , Tianyu He , Xin Li , Zhibo Chen

Constructing high-resolution 3D geological models from sparse 1D borehole and 2D surface data is a highly ill-posed inverse problem. Traditional heuristic and implicit modeling methods fundamentally fail to capture non-linear topological…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Zhixiang Lu , Mengqi Han , Peixin Guo , Tianming Bai , Jionglong Su , Fei Fang , Sifan Song

3D vision systems are fundamentally constrained by their reliance on visual overlap: reconstruction methods require it for geometric alignment, while generative models use it to enforce multi-view consistency. This limitation is…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Grzegorz Wilczynski , Mikołaj Zielinski , Bartosz Świrta , Dominik Belter , Przemysław Spurek

Neural rendering has advanced significantly in 3D reconstruction and novel view synthesis, and integrating physics into these frameworks opens new applications such as physically accurate digital twins for robotics and XR. However, the…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Daniel Rho , Jun Myeong Choi , Biswadip Dey , Roni Sengupta

Autoregressive models are structurally misaligned with the inherently parallel nature of geospatial understanding, forcing a rigid sequential narrative onto scenes and fundamentally hindering the generation of structured and coherent…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Jiaqi Liu , Ronghao Fu , Haoran Liu , Lang Sun , Bo Yang

Reconstructing dense geometry for dynamic scenes from a monocular video is a critical yet challenging task. Recent memory-based methods enable efficient online reconstruction, but they fundamentally suffer from a Memory Demand Dilemma: The…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Xudong Cai , Shuo Wang , Peng Wang , Yongcai Wang , Zhaoxin Fan , Wanting Li , Tianbao Zhang , Jianrong Tao , Yeying Jin , Deying Li

We present GaussFusion, a novel approach for improving 3D Gaussian splatting (3DGS) reconstructions in the wild through geometry-informed video generation. GaussFusion mitigates common 3DGS artifacts, including floaters, flickering, and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Liyuan Zhu , Manjunath Narayana , Michal Stary , Will Hutchcroft , Gordon Wetzstein , Iro Armeni

Recent advances in 3D Gaussian Splatting (3DGS) enable real-time, high-fidelity novel view synthesis (NVS) with explicit 3D representations. However, performance degradation and instability remain significant under sparse-view conditions.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Meixi Song , Xin Lin , Dizhe Zhang , Haodong Li , Xiangtai Li , Bo Du , Lu Qi