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Mirror-containing environments pose unique challenges for 3D reconstruction and novel view synthesis (NVS), as reflective surfaces introduce view-dependent distortions and inconsistencies. While cutting-edge methods such as Neural Radiance…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Zijing Guo , Yunyang Zhao , Lin Wang

Recent breakthroughs in radiance fields have significantly advanced 3D scene reconstruction and novel view synthesis (NVS) in autonomous driving. Nevertheless, critical limitations persist: reconstruction-based methods exhibit substantial…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Yingshuang Zou , Yikang Ding , Chuanrui Zhang , Jiazhe Guo , Bohan Li , Xiaoyang Lyu , Feiyang Tan , Xiaojuan Qi , Haoqian Wang

Differentiable 3D Gaussian splatting has emerged as an efficient and flexible rendering technique for representing complex scenes from a collection of 2D views and enabling high-quality real-time novel-view synthesis. However, its reliance…

Graphics · Computer Science 2025-01-16 Meenakshi Krishnan , Liam Fowl , Ramani Duraiswami

Recently, 3D Gaussian Splatting (3DGS) has enabled photorealistic view synthesis at high inference speeds. However, its splatting-based rendering model makes several approximations to the rendering equation, reducing physical accuracy. We…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Chinmay Talegaonkar , Yash Belhe , Ravi Ramamoorthi , Nicholas Antipa

This paper focuses on scene reconstruction under nighttime conditions in autonomous driving simulation. Recent methods based on Neural Radiance Fields (NeRFs) and 3D Gaussian Splatting (3DGS) have achieved photorealistic modeling in…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Tae-Kyeong Kim , Xingxin Chen , Guile Wu , Chengjie Huang , Dongfeng Bai , Bingbing Liu

Pre-training on large-scale unlabeled datasets contribute to the model achieving powerful performance on 3D vision tasks, especially when annotations are limited. However, existing rendering-based self-supervised frameworks are…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Hao Liu , Minglin Chen , Yanni Ma , Haihong Xiao , Ying He

Reconstructing dynamic scenes from video sequences is a highly promising task in the multimedia domain. While previous methods have made progress, they often struggle with slow rendering and managing temporal complexities such as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Jinbo Yan , Rui Peng , Luyang Tang , Ronggang Wang

We present the first unified framework for rate-distortion-optimized compression and segmentation of 3D Gaussian Splatting (3DGS). While 3DGS has proven effective for both real-time rendering and semantic scene understanding, prior works…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Yu-Jen Tseng , Chia-Hao Kao , Jing-Zhong Chen , Alessandro Gnutti , Shao-Yuan Lo , Yen-Yu Lin , Wen-Hsiao Peng

An excellent representation is crucial for reinforcement learning (RL) performance, especially in vision-based reinforcement learning tasks. The quality of the environment representation directly influences the achievement of the learning…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Jiaxu Wang , Qiang Zhang , Jingkai Sun , Jiahang Cao , Gang Han , Wen Zhao , Weining Zhang , Yecheng Shao , Yijie Guo , Renjing Xu

Recent advancements in 3D reconstruction coupled with neural rendering techniques have greatly improved the creation of photo-realistic 3D scenes, influencing both academic research and industry applications. The technique of 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Zexu Huang , Min Xu , Stuart Perry

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

We present GSD, a diffusion model approach based on Gaussian Splatting (GS) representation for 3D object reconstruction from a single view. Prior works suffer from inconsistent 3D geometry or mediocre rendering quality due to improper…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yuxuan Mu , Xinxin Zuo , Chuan Guo , Yilin Wang , Juwei Lu , Xiaofeng Wu , Songcen Xu , Peng Dai , Youliang Yan , Li Cheng

Reflective appearance, especially strong and typically near-field specular reflections, poses a fundamental challenge for accurate surface reconstruction and novel view synthesis. Existing Gaussian splatting methods either fail to model…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Ningjing Fan , Yiqun Wang , Dongming Yan , Peter Wonka

Gaussian splatting, renowned for its exceptional rendering quality and efficiency, has emerged as a prominent technique in 3D scene representation. However, the substantial data volume of Gaussian splatting impedes its practical utility in…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Xiangrui Liu , Xinju Wu , Pingping Zhang , Shiqi Wang , Zhu Li , Sam Kwong

Underwater image degradation poses significant challenges for 3D reconstruction, where simplified physical models often fail in complex scenes. We propose \textbf{R-Splatting}, a unified framework that bridges underwater image restoration…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Guoxi Huang , Haoran Wang , Zipeng Qi , Wenjun Lu , David Bull , Nantheera Anantrasirichai

We present a novel, hardware rasterized rendering approach for ray-based 3D Gaussian Splatting (RayGS), obtaining both fast and high-quality results for novel view synthesis. Our work contains a mathematically rigorous and geometrically…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Samuel Rota Bulò , Nemanja Bartolovic , Lorenzo Porzi , Peter Kontschieder

In the field of 3D dynamic scene reconstruction, how to balance model convergence rate and rendering quality has long been a critical challenge that urgently needs to be addressed, particularly in high-precision modeling of scenes with…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Nengbo Lu , Minghua Pan , Shaohua Sun , Yizhou Liang

Novel view synthesis has experienced significant advancements owing to increasingly capable NeRF- and 3DGS-based methods. However, reflective object reconstruction remains challenging, lacking a proper solution to achieve real-time,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Yuxuan Yao , Zixuan Zeng , Chun Gu , Xiatian Zhu , Li Zhang

3D Gaussian Splatting (3DGS) has demonstrated impressive performance in scene reconstruction. However, most existing GS-based surface reconstruction methods focus on 3D objects or limited scenes. Directly applying these methods to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Yuanyuan Gao , Yalun Dai , Hao Li , Weicai Ye , Junyi Chen , Danpeng Chen , Dingwen Zhang , Tong He , Guofeng Zhang , Junwei Han

Neural Radiance Fields (NeRFs) have demonstrated remarkable proficiency in synthesizing photorealistic images of large-scale scenes. However, they are often plagued by a loss of fine details and long rendering durations. 3D Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Zipeng Wang , Dan Xu