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We leverage 3D Gaussian Splatting (3DGS) as a scene representation and propose a novel test-time camera pose refinement (CPR) framework, GS-CPR. This framework enhances the localization accuracy of state-of-the-art absolute pose regression…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Changkun Liu , Shuai Chen , Yash Bhalgat , Siyan Hu , Ming Cheng , Zirui Wang , Victor Adrian Prisacariu , Tristan Braud

Novel view synthesis has advanced significantly with the development of neural radiance fields (NeRF) and 3D Gaussian splatting (3DGS). However, achieving high quality without compromising real-time rendering remains challenging,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhongpai Gao , Benjamin Planche , Meng Zheng , Anwesa Choudhuri , Terrence Chen , Ziyan Wu

We introduce GeoGS3D, a novel two-stage framework for reconstructing detailed 3D objects from single-view images. Inspired by the success of pre-trained 2D diffusion models, our method incorporates an orthogonal plane decomposition…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Qijun Feng , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

3D Gaussian Splatting (GS) enables highly photorealistic scene reconstruction from posed image sequences but struggles with viewpoint extrapolation due to its anisotropic nature, leading to overfitting and poor generalization, particularly…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Shuohan Tao , Boyao Zhou , Hanzhang Tu , Yuwang Wang , Yebin Liu

Feed-forward 3D Gaussian Splatting methods enable single-pass reconstruction and real-time rendering. However, they typically adopt rigid pixel-to-Gaussian or voxel-to-Gaussian pipelines that uniformly allocate Gaussians, leading to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Injae Kim , Chaehyeon Kim , Minseong Bae , Minseok Joo , Hyunwoo J. Kim

3D Gaussian Splatting reconstructs scenes by starting from a sparse Structure-from-Motion initialization and refining under-reconstructed regions. This process is slow, as it requires multiple densification steps where Gaussians are…

Graphics · Computer Science 2026-02-13 Dmytro Kotovenko , Olga Grebenkova , Björn Ommer

Conventional geometry-based SLAM systems lack dense 3D reconstruction capabilities since their data association usually relies on feature correspondences. Additionally, learning-based SLAM systems often fall short in terms of real-time…

Computer Vision and Pattern Recognition · Computer Science 2024-08-22 Zhongche Qu , Zhi Zhang , Cong Liu , Jianhua Yin

Reconstructing objects from posed images is a crucial and complex task in computer graphics and computer vision. While NeRF-based neural reconstruction methods have exhibited impressive reconstruction ability, they tend to be…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Shuichang Lai , Letian Huang , Jie Guo , Kai Cheng , Bowen Pan , Xiaoxiao Long , Jiangjing Lyu , Chengfei Lv , Yanwen Guo

3D Gaussian Splatting has emerged as a powerful representation of geometry and appearance for RGB-only dense Simultaneous Localization and Mapping (SLAM), as it provides a compact dense map representation while enabling efficient and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Erik Sandström , Keisuke Tateno , Michael Oechsle , Michael Niemeyer , Luc Van Gool , Martin R. Oswald , Federico Tombari

Recently, 2D Gaussian Splatting (2DGS) has demonstrated superior geometry reconstruction quality than the popular 3DGS by using 2D surfels to approximate thin surfaces. However, it falls short when dealing with glossy surfaces, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Yixin Yang , Yang Zhou , Hui Huang

3D Gaussian Splatting (3DGS) has revolutionized radiance field reconstruction by achieving high-quality novel view synthesis with fast rendering speed, introducing 3D Gaussian primitives to represent the scene. However, 3DGS encounters…

Graphics · Computer Science 2025-09-18 Yifan Mo , Youcheng Cai , Ligang Liu

The boundary representation (B-Rep) models a 3D solid as its explicit boundaries: trimmed corners, edges, and faces. Recovering B-Rep representation from unstructured data is a challenging and valuable task of computer vision and graphics.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Jiaxing Yu , Dongyang Ren , Hangyu Xu , Zhouyuxiao Yang , Yuanqi Li , Jie Guo , Zhengkang Zhou , Yanwen Guo

Although 3D Gaussian Splatting (3DGS) has achieved impressive performance in real-time rendering, its densification strategy often results in suboptimal reconstruction quality. In this work, we present a comprehensive improvement to the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Xiaobin Deng , Changyu Diao , Min Li , Ruohan Yu , Duanqing Xu

Gaussian splatting has achieved impressive improvements for both novel-view synthesis and surface reconstruction from multi-view images. However, current methods still struggle to reconstruct high-quality surfaces from only sparse view…

Computer Vision and Pattern Recognition · Computer Science 2024-12-23 Zhuowen Shen , Yuan Liu , Zhang Chen , Zhong Li , Jiepeng Wang , Yongqing Liang , Zhengming Yu , Jingdong Zhang , Yi Xu , Scott Schaefer , Xin Li , Wenping Wang

Multi-view mesh reconstruction remains a core challenge in computer graphics and vision, especially for recovering high-frequency geometry from sparse observations. Recent methods such as 3D Gaussian Splatting (3DGS) and Neural Radiance…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Nandhana Sunil , Abhirami R Iyer , Avirup Mandal

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

Rendering high-fidelity images from sparse point clouds is still challenging. Existing learning-based approaches suffer from either hole artifacts, missing details, or expensive computations. In this paper, we propose a novel framework to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Jiaxu Wang , Ziyi Zhang , Junhao He , Renjing Xu

Novel View Synthesis (NVS) from sparse views presents a formidable challenge in 3D reconstruction, where limited multi-view constraints lead to severe overfitting, geometric distortion, and fragmented scenes. While 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Yu Ma , Guoliang Wei , Haihong Xiao , Yue Cheng

Recent advancements in computer vision have successfully extended Open-vocabulary segmentation (OVS) to the 3D domain by leveraging 3D Gaussian Splatting (3D-GS). Despite this progress, efficiently rendering the high-dimensional features…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Yoonwoo Jeong , Cheng Sun , Frank Wang , Minsu Cho , Jaesung Choe

Generalizable 3D Gaussian Splatting has recently emerged as an efficient approach for novel-view synthesis, enabling feed-forward synthesis from only a few input views. However, existing pixel-wise feed-forward methods suffer from…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Hoang Chuong Nguyen , Renjie Wu , Jose M. Alvarez , Miaomiao Liu