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3D Gaussian Splatting (3DGS) has recently transformed photorealistic reconstruction, achieving high visual fidelity and real-time performance. However, rendering quality significantly deteriorates when test views deviate from the camera…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yutong Chen , Marko Mihajlovic , Xiyi Chen , Yiming Wang , Sergey Prokudin , Siyu Tang

Generalizable 3D Gaussian Splatting reconstruction showcases advanced Image-to-3D content creation but requires substantial computational resources and large datasets, posing challenges to training models from scratch. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Xiufeng Huang , Ka Chun Cheung , Runmin Cong , Simon See , Renjie Wan

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

Despite recent progress in 3D head avatar generation, balancing identity preservation, i.e., reconstruction, with novel poses and expressions, i.e., animation, remains a challenge. Existing methods struggle to adapt Gaussians to varying…

Graphics · Computer Science 2025-07-25 SeungJun Moon , Hah Min Lew , Seungeun Lee , Ji-Su Kang , Gyeong-Moon Park

3D Gaussian Splatting has recently been embraced as a versatile and effective method for scene reconstruction and novel view synthesis, owing to its high-quality results and compatibility with hardware rasterization. Despite its advantages,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Yalda Foroutan , Daniel Rebain , Kwang Moo Yi , Andrea Tagliasacchi

We present SplattingAvatar, a hybrid 3D representation of photorealistic human avatars with Gaussian Splatting embedded on a triangle mesh, which renders over 300 FPS on a modern GPU and 30 FPS on a mobile device. We disentangle the motion…

Graphics · Computer Science 2024-03-11 Zhijing Shao , Zhaolong Wang , Zhuang Li , Duotun Wang , Xiangru Lin , Yu Zhang , Mingming Fan , Zeyu Wang

3D modeling of highly reflective objects remains challenging due to strong view-dependent appearances. While previous SDF-based methods can recover high-quality meshes, they are often time-consuming and tend to produce over-smoothed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Jinguang Tong , Xuesong li , Fahira Afzal Maken , Sundaram Muthu , Lars Petersson , Chuong Nguyen , Hongdong Li

Accurate geometric surface reconstruction, providing essential environmental information for navigation and manipulation tasks, is critical for enabling robotic self-exploration and interaction. Recently, 3D Gaussian Splatting (3DGS) has…

Computer Vision and Pattern Recognition · Computer Science 2025-07-17 Tengfei Wang , Xin Wang , Yongmao Hou , Zhaoning Zhang , Yiwei Xu , Zongqian Zhan

3D Gaussian Splatting (3DGS) has shown promising performance in novel view synthesis. Previous methods adapt it to obtaining surfaces of either individual 3D objects or within limited scenes. In this paper, we make the first attempt to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Junyi Chen , Weicai Ye , Yifan Wang , Danpeng Chen , Di Huang , Wanli Ouyang , Guofeng Zhang , Yu Qiao , Tong He

3D scene reconstruction is fundamental for spatial intelligence applications such as AR, robotics, and digital twins. Traditional multi-view stereo struggles with sparse viewpoints or low-texture regions, while neural rendering approaches,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Jiaqi Yao , Zhongmiao Yan , Jingyi Xu , Songpengcheng Xia , Yan Xiang , Ling Pei

We present SplatCo, a structure-view collaborative Gaussian splatting framework for high-fidelity rendering of complex outdoor scenes. SplatCo builds upon three novel components: 1) a cross-structure collaboration module that combines…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Haihong Xiao , Jianan Zou , Yuxin Zhou , Ying He , Wenxiong Kang

Recently, the integration of the efficient feed-forward scheme into 3D Gaussian Splatting (3DGS) has been actively explored. However, most existing methods focus on sparse view reconstruction of small regions and cannot produce eligible…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee Lee

High-fidelity 3D reconstruction of common indoor scenes is crucial for VR and AR applications. 3D Gaussian splatting, a novel differentiable rendering technique, has achieved state-of-the-art novel view synthesis results with high rendering…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Matias Turkulainen , Xuqian Ren , Iaroslav Melekhov , Otto Seiskari , Esa Rahtu , Juho Kannala

3D Gaussian Splatting (3DGS) has emerged as a promising approach for 3D scene representation, offering a reduction in computational overhead compared to Neural Radiance Fields (NeRF). However, 3DGS is susceptible to high-frequency artifacts…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Shen Chen , Jiale Zhou , Lei Li

Reconstructing 3D scenes from sparse viewpoints is a long-standing challenge with wide applications. Recent advances in feed-forward 3D Gaussian sparse-view reconstruction methods provide an efficient solution for real-time novel view…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Yang Xiao , Guoan Xu , Qiang Wu , Wenjing Jia

Rendering novel view images in dynamic scenes is a crucial yet challenging task. Current methods mainly utilize NeRF-based methods to represent the static scene and an additional time-variant MLP to model scene deformations, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Diwen Wan , Ruijie Lu , Gang Zeng

3D Gaussian Splatting (3DGS) has revolutionized fast novel view synthesis, yet its opacity-based formulation makes surface extraction fundamentally difficult. Unlike implicit methods built on Signed Distance Fields or occupancy, 3DGS lacks…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Diego Gomez , Antoine Guédon , Nissim Maruani , Bingchen Gong , Maks Ovsjanikov

Embodied intelligence requires precise reconstruction and rendering to simulate large-scale real-world data. Although 3D Gaussian Splatting (3DGS) has recently demonstrated high-quality results with real-time performance, it still faces…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Haodong Xiang , Xinghui Li , Kai Cheng , Xiansong Lai , Wanting Zhang , Zhichao Liao , Long Zeng , Xueping Liu

In this paper, we introduce Splatt3R, a pose-free, feed-forward method for in-the-wild 3D reconstruction and novel view synthesis from stereo pairs. Given uncalibrated natural images, Splatt3R can predict 3D Gaussian Splats without…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Brandon Smart , Chuanxia Zheng , Iro Laina , Victor Adrian Prisacariu

Low-light 3D reconstruction from sparse views remains challenging due to exposure imbalance and degraded color fidelity. While existing methods struggle with view inconsistency and require per-scene training, we propose SplatBright, which…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Yue Wen , Liang Song , Hesheng Wang
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