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Related papers: FTSplat: Feed-forward Triangle Splatting Network

200 papers

Accurate 3D reconstruction in degraded imaging conditions remains a key challenge in photogrammetry and neural rendering. In underwater environments, spatially varying visibility caused by scattering, attenuation, and sparse observations…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Zhuodong Jiang , Haoran Wang , Guoxi Huang , Brett Seymour , Nantheera Anantrasirichai

We present latentSplat, a method to predict semantic Gaussians in a 3D latent space that can be splatted and decoded by a light-weight generative 2D architecture. Existing methods for generalizable 3D reconstruction either do not scale to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Christopher Wewer , Kevin Raj , Eddy Ilg , Bernt Schiele , Jan Eric Lenssen

3D object generation from a single image involves estimating the full 3D geometry and texture of unseen views from an unposed RGB image captured in the wild. Accurately reconstructing an object's complete 3D structure and texture has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Hritam Basak , Hadi Tabatabaee , Shreekant Gayaka , Ming-Feng Li , Xin Yang , Cheng-Hao Kuo , Arnie Sen , Min Sun , Zhaozheng Yin

The 3D Gaussian Splatting technique has significantly advanced the construction of radiance fields from multi-view images, enabling real-time rendering. While point-based rasterization effectively reduces computational demands for…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Jiaze Li , Zhengyu Wen , Luo Zhang , Jiangbei Hu , Fei Hou , Zhebin Zhang , Ying He

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

While 3D Gaussian Splatting (3DGS) enables high-quality, real-time rendering for bounded scenes, its extension to large-scale urban environments gives rise to critical challenges in terms of geometric consistency, memory efficiency, and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Changbai Li , Haodong Zhu , Hanlin Chen , Xiuping Liang , Tongfei Chen , Shuwei Shao , Linlin Yang , Huobin Tan , Baochang Zhang

Achieving high-fidelity 3D reconstruction from monocular video remains challenging due to the inherent limitations of traditional methods like Structure-from-Motion (SfM) and monocular SLAM in accurately capturing scene details. While…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Yue Hu , Rong Liu , Meida Chen , Peter Beerel , Andrew Feng

Sparse-view reconstruction models typically require precise camera poses, yet obtaining these parameters from sparse-view images remains challenging. We introduce FreeSplatter, a scalable feed-forward framework that generates high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Jiale Xu , Shenghua Gao , Ying Shan

Novel view synthesis has recently been revolutionized by 3D Gaussian Splatting (3DGS), which enables real-time rendering through explicit primitive rasterization. However, existing methods tie visual fidelity strictly to the number of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Mihnea-Bogdan Jurca , Bert Van hauwermeiren , Adrian Munteanu

3D Gaussian Splatting (3DGS) has made significant strides in real-time 3D scene reconstruction, but faces memory scalability issues in high-resolution scenarios. To address this, we propose Hierarchical Gaussian Splatting (HRGS), a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Changbai Li , Haodong Zhu , Hanlin Chen , Juan Zhang , Tongfei Chen , Shuo Yang , Shuwei Shao , Wenhao Dong , Baochang Zhang

Sparse-view 3D Gaussian splatting seeks to render high-quality novel views of 3D scenes from a limited set of input images. While recent pose-free feed-forward methods leveraging pre-trained 3D priors have achieved impressive results, most…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Muyu Xu , Fangneng Zhan , Xiaoqin Zhang , Ling Shao , Shijian Lu

Real-time, high-fidelity reconstruction of dynamic driving scenes is challenged by complex dynamics and sparse views, with prior methods struggling to balance quality and efficiency. We propose DrivingScene, an online, feed-forward…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Qirui Hou , Wenzhang Sun , Chang Zeng , Chunfeng Wang , Hao Li , Jianxun Cui

We introduce OceanSplat, a novel 3D Gaussian Splatting-based approach for high-fidelity underwater scene reconstruction. To overcome multi-view inconsistencies caused by scattering media, we design a trinocular setup for each camera pose by…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Minseong Kweon , Jinsun Park

We propose WildSplatter, a feed-forward 3D Gaussian Splatting (3DGS) model for unconstrained images with unknown camera parameters and varying lighting conditions. 3DGS is an effective scene representation that enables high-quality,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Yuki Fujimura , Takahiro Kushida , Kazuya Kitano , Takuya Funatomi , Yasuhiro Mukaigawa

Gaussian Splatting (GS) has proven to be highly effective in novel view synthesis, achieving high-quality and real-time rendering. However, its potential for reconstructing detailed 3D shapes has not been fully explored. Existing methods…

Graphics · Computer Science 2024-06-25 Baowen Zhang , Chuan Fang , Rakesh Shrestha , Yixun Liang , Xiaoxiao Long , Ping Tan

Per-scene optimization methods such as 3D Gaussian Splatting provide state-of-the-art novel view synthesis quality but extrapolate poorly to under-observed areas. Methods that leverage generative priors to correct artifacts in these areas…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Riccardo de Lutio , Tobias Fischer , Yen-Yu Chang , Yuxuan Zhang , Jay Zhangjie Wu , Xuanchi Ren , Tianchang Shen , Katarina Tothova , Zan Gojcic , Haithem Turki

The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes explicitly as collections of 3D Gaussians, 3DGS enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Vitor Pereira Matias , Daniel Perazzo , Vinicius Silva , Alberto Raposo , Luiz Velho , Afonso Paiva , Tiago Novello

Recent trends in SLAM and visual navigation have embraced 3D Gaussians as the preferred scene representation, highlighting the importance of estimating camera poses from a single image using a pre-built Gaussian model. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Hao Wang , Linqing Zhao , Xiuwei Xu , Jiwen Lu , Haibin Yan

In the realm of robot-assisted minimally invasive surgery, dynamic scene reconstruction can significantly enhance downstream tasks and improve surgical outcomes. Neural Radiance Fields (NeRF)-based methods have recently risen to prominence…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Yiming Huang , Beilei Cui , Long Bai , Ziqi Guo , Mengya Xu , Mobarakol Islam , Hongliang Ren

3D Gaussian Splatting has demonstrated remarkable real-time rendering capabilities and superior visual quality in novel view synthesis for static scenes. Building upon these advantages, researchers have progressively extended 3D Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Han Jiao , Jiakai Sun , Lei Zhao , Zhanjie Zhang , Wei Xing , Huaizhong Lin