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3D Gaussian Splatting (3DGS) achieves remarkable results in the field of surface reconstruction. However, when Gaussian normal vectors are aligned within the single-view projection plane, while the geometry appears reasonable in the current…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Bo Jia , Yanan Guo , Ying Chang , Benkui Zhang , Ying Xie , Kangning Du , Lin Cao

Although 3D Gaussian Splatting (3D-GS) achieves efficient rendering for novel view synthesis, extending it to dynamic scenes still results in substantial memory overhead from replicating Gaussians across frames. To address this challenge,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Chun-Tin Wu , Jun-Cheng Chen

Understanding 3D scenes is pivotal for autonomous driving, robotics, and augmented reality. Recent semantic Gaussian Splatting approaches leverage large-scale 2D vision models to project 2D semantic features onto 3D scenes. However, they…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Tianyu Huang , Runnan Chen , Dongting Hu , Fengming Huang , Mingming Gong , Tongliang Liu

Reconstructing intricate, ever-changing environments remains a central ambition in computer vision, yet existing solutions often crumble before the complexity of real-world dynamics. We present DynaSplat, an approach that extends Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Junli Deng , Ping Shi , Qipei Li , Jinyang Guo

Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gaussian Splatting have achieved fine-grained reconstruction and high-fidelity novel view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Yuru Xiao , Zihan Lin , Chao Lu , Deming Zhai , Kui Jiang , Wenbo Zhao , Wei Zhang , Junjun Jiang , Huanran Wang , Xianming Liu

3D Gaussian Splatting (3DGS) has gained significant attention for its real-time, photo-realistic rendering in novel-view synthesis and 3D modeling. However, existing methods struggle with accurately modeling scenes affected by transient…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Chuanyu Fu , Yuqi Zhang , Kunbin Yao , Guanying Chen , Yuan Xiong , Chuan Huang , Shuguang Cui , Xiaochun Cao

Recent advancements in 3D editing have highlighted the potential of text-driven methods in real-time, user-friendly AR/VR applications. However, current methods rely on 2D diffusion models without adequately considering multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Dong In Lee , Hyeongcheol Park , Jiyoung Seo , Eunbyung Park , Hyunje Park , Ha Dam Baek , Sangheon Shin , Sangmin Kim , Sangpil Kim

Image-based 3D reconstruction is a challenging task that involves inferring the 3D shape of an object or scene from a set of input images. Learning-based methods have gained attention for their ability to directly estimate 3D shapes. This…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Anurag Dalal , Daniel Hagen , Kjell G. Robbersmyr , Kristian Muri Knausgård

Feed-forward 3D Gaussian Splatting (3DGS) has shown great promise for real-time novel view synthesis, but its application to panoramic imagery remains challenging. Existing methods often rely on multi-view cost volumes for geometric…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Qiwei Wang , Xianghui Ze , Jingyi Yu , Yujiao Shi

Recent advancements in multi-view 3D reconstruction and novel-view synthesis, particularly through Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), have greatly enhanced the fidelity and efficiency of 3D content creation.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Jun Zhou , Dinghao Li , Nannan Li , Mingjie Wang

Surface reconstruction is fundamental to computer vision and graphics, enabling applications in 3D modeling, mixed reality, robotics, and more. Existing approaches based on volumetric rendering obtain promising results, but optimize on a…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Yueh-Cheng Liu , Lukas Höllein , Matthias Nießner , Angela Dai

3D Gaussian Splatting (3D-GS) has demonstrated exceptional capabilities in 3D scene reconstruction and novel view synthesis. However, its training heavily depends on high-quality, sharp images and accurate camera poses. Fulfilling these…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Wangbo Yu , Chaoran Feng , Jiye Tang , Jiashu Yang , Zhenyu Tang , Xu Jia , Yuchao Yang , Li Yuan , Yonghong Tian

Photorealistic 3D reconstruction of street scenes is a critical technique for developing real-world simulators for autonomous driving. Despite the efficacy of Neural Radiance Fields (NeRF) for driving scenes, 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Nan Huang , Xiaobao Wei , Wenzhao Zheng , Pengju An , Ming Lu , Wei Zhan , Masayoshi Tomizuka , Kurt Keutzer , Shanghang Zhang

Recent advancements in 3D Gaussian Splatting (3DGS) have demonstrated its potential for efficient and photorealistic 3D reconstructions, which is crucial for diverse applications such as robotics and immersive media. However, current…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Daheng Yin , Isaac Ding , Yili Jin , Jianxin Shi , Jiangchuan Liu

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

While Gaussian Splatting (GS) demonstrates efficient and high-quality scene rendering and small area surface extraction ability, it falls short in handling large-scale aerial image surface extraction tasks. To overcome this, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Zhuoxiao Li , Shanliang Yao , Taoyu Wu , Yong Yue , Wufan Zhao , Rongjun Qin , Angel F. Garcia-Fernandez , Andrew Levers , Xiaohui Zhu

Recognizing arbitrary or previously unseen categories is essential for comprehensive real-world 3D scene understanding. Currently, all existing methods rely on 2D or textual modalities during training or together at inference. This…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Yue Li , Qi Ma , Runyi Yang , Huapeng Li , Mengjiao Ma , Bin Ren , Nikola Popovic , Nicu Sebe , Ender Konukoglu , Theo Gevers , Luc Van Gool , Martin R. Oswald , Danda Pani Paudel

Recent advances in real-time neural rendering using point-based techniques have enabled broader adoption of 3D representations. However, foundational approaches like 3D Gaussian Splatting impose substantial storage overhead, as…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zhiwen Fan , Kevin Wang , Kairun Wen , Zehao Zhu , Dejia Xu , Zhangyang Wang

Gaussian Splatting has achieved remarkable progress in multi-view surface reconstruction, yet it exhibits notable degradation when only few views are available. Although recent efforts alleviate this issue by enhancing multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jimin Tang , Wenyuan Zhang , Junsheng Zhou , Zian Huang , Kanle Shi , Shenkun Xu , Yu-Shen Liu , Zhizhong Han

Recent advancements in 3D reconstruction technologies have paved the way for high-quality and real-time rendering of complex 3D scenes. Despite these achievements, a notable challenge persists: it is difficult to precisely reconstruct…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Lizhi Wang , Feng Zhou , Bo yu , Pu Cao , Jianqin Yin
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