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3D Gaussian Splatting (3DGS) effectively synthesizes novel views through its flexible representation, yet fails to accurately reconstruct scene geometry. While modern variants like PGSR introduce additional losses to ensure proper depth and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Zhentao Huang , Di Wu , Zhenbang He , Minglun Gong

3D fragment reassembly aims to recover the rigid poses of unordered fragment point clouds or meshes in a common object coordinate system to reconstruct the complete shape. The problem becomes particularly challenging as the number of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Hanze Jia , Chunshi Wang , Yuxiao Yang , Zhonghua Jiang , Yawei Luo , Shuainan Ye , Tan Tang

Recent advances in 3D Gaussian Splatting (3DGS) have enabled efficient free-viewpoint rendering and photorealistic scene reconstruction. While on-the-fly extensions of 3DGS have shown promise for real-time reconstruction from monocular RGB…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Yijia Guo , Tong Hu , Zhiwei Li , Liwen Hu , Keming Qian , Xitong Lin , Shengbo Chen , Tiejun Huang , Lei Ma

3D Gaussian Splatting (3DGS) has emerged as a powerful paradigm for real-time and high-fidelity 3D reconstruction from posed images. However, recent studies reveal its vulnerability to adversarial corruptions in input views, where…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Yiran Qiao , Yiren Lu , Yunlai Zhou , Rui Yang , Linlin Hou , Yu Yin , Jing Ma

Humans can infer 3D structure from 2D images of an object based on past experience and improve their 3D understanding as they see more images. Inspired by this behavior, we introduce SAP3D, a system for 3D reconstruction and novel view…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Xinyang Han , Zelin Gao , Angjoo Kanazawa , Shubham Goel , Yossi Gandelsman

We present the first application of 3D Gaussian Splatting in monocular SLAM, the most fundamental but the hardest setup for Visual SLAM. Our method, which runs live at 3fps, utilises Gaussians as the only 3D representation, unifying the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Hidenobu Matsuki , Riku Murai , Paul H. J. Kelly , Andrew J. Davison

3D reassembly is a challenging spatial intelligence task with broad applications across scientific domains. While large-scale synthetic datasets have fueled promising learning-based approaches, their generalizability to different domains is…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Sihang Li , Zeyu Jiang , Grace Chen , Chenyang Xu , Siqi Tan , Xue Wang , Irving Fang , Kristof Zyskowski , Shannon P. McPherron , Radu Iovita , Chen Feng , Jing Zhang

Recently, 3D Gaussian splatting (3DGS) has gained considerable attentions in the field of novel view synthesis due to its fast performance while yielding the excellent image quality. However, 3DGS in sparse-view settings (e.g., three-view…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Hyunwoo Park , Gun Ryu , Wonjun Kim

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

Drones have become essential tools for reconstructing wild scenes due to their outstanding maneuverability. Recent advances in radiance field methods have achieved remarkable rendering quality, providing a new avenue for 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Jiadong Tang , Yu Gao , Dianyi Yang , Liqi Yan , Yufeng Yue , Yi Yang

3D Gaussian Splatting (3DGS) has begun incorporating rich information from 2D foundation models. However, most approaches rely on a bottom-up optimization process that treats raw 2D features as ground truth, incurring increased…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Hyunjoon Lee , Joonkyu Min , Jaesik Park

We propose 3D Super Resolution (3DSR), a novel 3D Gaussian-splatting-based super-resolution framework that leverages off-the-shelf diffusion-based 2D super-resolution models. 3DSR encourages 3D consistency across views via the use of an…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Yi-Ting Chen , Ting-Hsuan Liao , Pengsheng Guo , Alexander Schwing , Jia-Bin Huang

In this paper, we propose a 3D geometry-aware deformable Gaussian Splatting method for dynamic view synthesis. Existing neural radiance fields (NeRF) based solutions learn the deformation in an implicit manner, which cannot incorporate 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Zhicheng Lu , Xiang Guo , Le Hui , Tianrui Chen , Min Yang , Xiao Tang , Feng Zhu , Yuchao Dai

3D Gaussian Splatting has recently achieved notable success in novel view synthesis for dynamic scenes and geometry reconstruction in static scenes. Building on these advancements, early methods have been developed for dynamic surface…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Decai Chen , Brianne Oberson , Ingo Feldmann , Oliver Schreer , Anna Hilsmann , Peter Eisert

In this paper, we present an implicit surface reconstruction method with 3D Gaussian Splatting (3DGS), namely 3DGSR, that allows for accurate 3D reconstruction with intricate details while inheriting the high efficiency and rendering…

Computer Vision and Pattern Recognition · Computer Science 2025-01-24 Xiaoyang Lyu , Yang-Tian Sun , Yi-Hua Huang , Xiuzhe Wu , Ziyi Yang , Yilun Chen , Jiangmiao Pang , Xiaojuan Qi

Accurate 3D reconstruction of vehicles is vital for applications such as vehicle inspection, predictive maintenance, and urban planning. Existing methods like Neural Radiance Fields and Gaussian Splatting have shown impressive results but…

Computer Vision and Pattern Recognition · Computer Science 2025-07-17 Davide Di Nucci , Matteo Tomei , Guido Borghi , Luca Ciuffreda , Roberto Vezzani , Rita Cucchiara

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

3D Gaussian Splatting (3DGS) is a powerful reconstruction technique, but it needs to be initialized from accurate camera poses and high-fidelity point clouds. Typically, the initialization is taken from Structure-from-Motion (SfM)…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Jizong Peng , Tze Ho Elden Tse , Kai Xu , Wenchao Gao , Angela Yao

We present WinT3R, a feed-forward reconstruction model capable of online prediction of precise camera poses and high-quality point maps. Previous methods suffer from a trade-off between reconstruction quality and real-time performance. To…

Computer Vision and Pattern Recognition · Computer Science 2025-09-08 Zizun Li , Jianjun Zhou , Yifan Wang , Haoyu Guo , Wenzheng Chang , Yang Zhou , Haoyi Zhu , Junyi Chen , Chunhua Shen , Tong He

We introduce a new task, Map and Locate, which unifies the traditionally distinct objectives of open-vocabulary segmentation - detecting and segmenting object instances based on natural language queries - and 3D reconstruction, the process…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Xuweiyi Chen , Tian Xia , Sihan Xu , Jianing Yang , Joyce Chai , Zezhou Cheng