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Recent advances in data-driven geometric multi-view 3D reconstruction foundation models (e.g., DUSt3R) have shown remarkable performance across various 3D vision tasks, facilitated by the release of large-scale, high-quality 3D datasets.…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Wenyu Li , Sidun Liu , Peng Qiao , Yong Dou

Building models are conventionally reconstructed by building roof points planar segmentation and then using a topology graph to group the planes together. Roof edges and vertices are then mathematically represented by intersecting segmented…

Computer Vision and Pattern Recognition · Computer Science 2020-10-16 Zhixin Li , Wenyuan Zhang , Jie Shan

For architectural design, representation across multiple Levels of Details (LoD) is essential for achieving a smooth transition from conceptual massing to detailed modeling. However, traditional LoD modeling processes rely on manual…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Xusheng Du , Athiwat Kongkaeo , Ye Zhang , Haoran Xie

We present NOVA3R, an effective approach for non-pixel-aligned 3D reconstruction from a set of unposed images in a feed-forward manner. Unlike pixel-aligned methods that tie geometry to per-ray predictions, our formulation learns a global,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Weirong Chen , Chuanxia Zheng , Ganlin Zhang , Andrea Vedaldi , Daniel Cremers

We propose a method for 3D object reconstruction and 6D-pose estimation from 2D images that uses knowledge about object shape as the primary key. In the proposed pipeline, recognition and labeling of objects in 2D images deliver 2D segment…

Computer Vision and Pattern Recognition · Computer Science 2022-03-03 Marcell Wolnitza , Osman Kaya , Tomas Kulvicius , Florentin Wörgötter , Babette Dellen

Reconstructing 3D objects from a single image is an intriguing but challenging problem. One promising solution is to utilize multi-view (MV) 3D reconstruction to fuse generated MV images into consistent 3D objects. However, the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Yizheng Chen , Rengan Xie , Qi Ye , Sen Yang , Zixuan Xie , Tianxiao Chen , Rong Li , Yuchi Huo

Feed-forward 3D reconstruction has revolutionized 3D vision, providing a powerful baseline for downstream tasks such as novel-view synthesis with 3D Gaussian Splatting. Previous works explore fixing the corrupted rendering results with a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Yiming Huang , Baixiang Huang , Beilei Cui , Chi Kit Ng , Long Bai , Hongliang Ren

Recent learning approaches that implicitly represent surface geometry using coordinate-based neural representations have shown impressive results in the problem of multi-view 3D reconstruction. The effectiveness of these techniques is,…

Computer Vision and Pattern Recognition · Computer Science 2021-07-28 Eduard Ramon , Gil Triginer , Janna Escur , Albert Pumarola , Jaime Garcia , Xavier Giro-i-Nieto , Francesc Moreno-Noguer

Large Reconstruction Models have made significant strides in the realm of automated 3D content generation from single or multiple input images. Despite their success, these models often produce 3D meshes with geometric inaccuracies,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Ruikai Cui , Xibin Song , Weixuan Sun , Senbo Wang , Weizhe Liu , Shenzhou Chen , Taizhang Shang , Yang Li , Nick Barnes , Hongdong Li , Pan Ji

3D spatial perception is fundamental to generalizable robotic manipulation, yet obtaining reliable, high-quality 3D geometry remains challenging. Depth sensors suffer from noise and material sensitivity, while existing reconstruction models…

Robotics · Computer Science 2026-05-05 Sizhe Yang , Linning Xu , Hao Li , Juncheng Mu , Jia Zeng , Dahua Lin , Jiangmiao Pang

Recent advances in dense 3D reconstruction have led to significant progress, yet achieving accurate unified geometric prediction remains a major challenge. Most existing methods are limited to predicting a single geometry quantity from…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Xianze Fang , Jingnan Gao , Zhe Wang , Zhuo Chen , Xingyu Ren , Jiangjing Lyu , Qiaomu Ren , Zhonglei Yang , Xiaokang Yang , Yichao Yan , Chengfei Lyu

In this paper, we present a novel indoor 3D reconstruction method with occluded surface completion, given a sequence of depth readings. Prior state-of-the-art (SOTA) methods only focus on the reconstruction of the visible areas in a scene,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Su Sun , Cheng Zhao , Yuliang Guo , Ruoyu Wang , Xinyu Huang , Yingjie Victor Chen , Liu Ren

Monocular 3D building reconstruction from remote sensing imagery is essential for scalable urban modeling, yet existing methods often require task-specific architectures and intensive supervision. This paper presents the first systematic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Junsheng Yao , Lichao Mou , Qingyu Li

In the reconstruction of fa\c{c}ade elements, the identification of specific object types remains challenging and is often circumvented by rectangularity assumptions or the use of bounding boxes. We propose a new approach for the…

Computer Vision and Pattern Recognition · Computer Science 2024-02-12 Thomas Froech , Olaf Wysocki , Ludwig Hoegner , Uwe Stilla

Level of Detail (LoD) is a fundamental technique in real-time computer graphics for managing the rendering costs of complex scenes while preserving visual fidelity. Traditionally, LoD is implemented using discrete levels (DLoD), where…

Graphics · Computer Science 2026-04-02 Zhigang Cheng , Mingchao Sun , Yu Liu , Zengye Ge , Luyang Tang , Mu Xu , Yangyan Li , Peng Pan

3D reconstruction from single view images is an ill-posed problem. Inferring the hidden regions from self-occluded images is both challenging and ambiguous. We propose a two-pronged approach to address these issues. To better incorporate…

Computer Vision and Pattern Recognition · Computer Science 2019-03-27 Priyanka Mandikal , K L Navaneet , Mayank Agarwal , R. Venkatesh Babu

Despite recent advances in feed-forward 3D Gaussian Splatting, generalizable 3D reconstruction remains challenging, particularly in multi-view correspondence modeling. Existing approaches face a fundamental trade-off: explicit methods…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Heng Jia , Linchao Zhu , Na Zhao

Range-view (RV) based LiDAR diffusion has recently made huge strides towards 2D photo-realism. However, it neglects 3D geometry realism and often generates various RV artifacts such as depth bleeding and wavy surfaces. We design L3DR, a…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Quan Liu , Xiaoqin Zhang , Ling Shao , Shijian Lu

Recent advances in 2D-to-3D perception have enabled the recovery of 3D scene semantics from unposed images. However, prevailing methods often suffer from limited generalization, reliance on per-scene optimization, and semantic…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Jie Hu , Shizun Wang , Xinchao Wang

With the rapid development of computer graphics and vision, several three-dimensional (3D) reconstruction techniques have been proposed and used to obtain the 3D representation of objects in the form of point cloud models, mesh models, and…

Computer Vision and Pattern Recognition · Computer Science 2021-12-02 Rui Wang