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While Gaussian Splatting-based Feature Fields (GSFFs) have shown promise for visual localization, this paper highlights that photometrically optimized GSFFs are inherently ill-suited for 2D-3D matching. The volumetric extent of each…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Miso Lee , Sangeek Hyun , Yerim Jeon , Jae-Pil Heo

We have introduced SegSplat, a novel framework designed to bridge the gap between rapid, feed-forward 3D reconstruction and rich, open-vocabulary semantic understanding. By constructing a compact semantic memory bank from multi-view 2D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Peter Siegel , Federico Tombari , Marc Pollefeys , Daniel Barath

We present Free-Range Gaussians, a multi-view reconstruction method that predicts non-pixel, non-voxel-aligned 3D Gaussians from as few as four images. This is done through flow matching over Gaussian parameters. Our generative formulation…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Ahan Shabanov , Peter Hedman , Ethan Weber , Zhengqin Li , Denis Rozumny , Gael Le Lan , Naina Dhingra , Lei Luo , Andrea Vedaldi , Christian Richardt , Andrea Tagliasacchi , Bo Zhu , Numair Khan

Most 3D Gaussian Splatting (3D-GS) based methods for urban scenes initialize 3D Gaussians directly with 3D LiDAR points, which not only underutilizes LiDAR data capabilities but also overlooks the potential advantages of fusing LiDAR with…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Cheng Zhao , Su Sun , Ruoyu Wang , Yuliang Guo , Jun-Jun Wan , Zhou Huang , Xinyu Huang , Yingjie Victor Chen , Liu Ren

We propose the task of Panoptic Scene Completion (PSC) which extends the recently popular Semantic Scene Completion (SSC) task with instance-level information to produce a richer understanding of the 3D scene. Our PSC proposal utilizes a…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Anh-Quan Cao , Angela Dai , Raoul de Charette

Open-vocabulary scene understanding using 3D Gaussian (3DGS) representations has garnered considerable attention. However, existing methods mostly lift knowledge from large 2D vision models into 3DGS on a scene-by-scene basis, restricting…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Runnan Chen , Xiangyu Sun , Zhaoqing Wang , Youquan Liu , Jiepeng Wang , Lingdong Kong , Jiankang Deng , Mingming Gong , Liang Pan , Wenping Wang , Tongliang Liu

In the domain of 3D scene representation, 3D Gaussian Splatting (3DGS) has emerged as a pivotal technology. However, its application to large-scale, high-resolution scenes (exceeding 4k$\times$4k pixels) is hindered by the excessive…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Wenkai Liu , Tao Guan , Bin Zhu , Lili Ju , Zikai Song , Dan Li , Yuesong Wang , Wei Yang

3D Gaussians have recently emerged as an effective scene representation for real-time splatting and accurate novel-view synthesis, motivating several works to adapt multi-view structure prediction networks to regress per-pixel 3D Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Mehdi Hosseinzadeh , Shin-Fang Chng , Yi Xu , Simon Lucey , Ian Reid , Ravi Garg

Gaussian Splatting has rapidly emerged as a transformative technique for real-time 3D scene representation, offering a highly efficient and expressive alternative to Neural Radiance Fields (NeRF). Its ability to render complex scenes with…

Graphics · Computer Science 2025-08-20 Mahmoud Chick Zaouali , Todd Charter , Yehor Karpichev , Brandon Haworth , Homayoun Najjaran

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

3D Semantic Scene Completion (SSC) can provide dense geometric and semantic scene representations, which can be applied in the field of autonomous driving and robotic systems. It is challenging to estimate the complete geometry and…

Computer Vision and Pattern Recognition · Computer Science 2023-02-28 Ruihang Miao , Weizhou Liu , Mingrui Chen , Zheng Gong , Weixin Xu , Chen Hu , Shuchang Zhou

Neural rendering techniques have made substantial progress in generating photo-realistic 3D scenes. The latest 3D Gaussian Splatting technique has achieved high quality novel view synthesis as well as fast rendering speed. However, 3D…

Graphics · Computer Science 2025-05-09 Xinran Yang , Donghao Ji , Yuanqi Li , Jie Guo , Yanwen Guo , Junyuan Xie

3D Gaussian Splatting (3DGS) has emerged as a promising representation for photorealistic rendering of 3D scenes. However, its high storage requirements pose significant challenges for practical applications. We observe that Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2025-11-05 Yuang Shi , Simone Gasparini , Géraldine Morin , Chenggang Yang , Wei Tsang Ooi

Modern vision language pipelines are driven by RGB vision encoders trained on massive image text corpora. While these pipelines have enabled impressive zero-shot capabilities and strong transfer across tasks, they still inherit two…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Yasmine Omri , Connor Ding , Tsachy Weissman , Thierry Tambe

Feed-forward 3D Gaussian Splatting (3DGS) enables efficient one-pass scene reconstruction, providing 3D representations for novel view synthesis without per-scene optimization. However, existing methods typically predict pixel-aligned…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Jongmin Park , Minh-Quan Viet Bui , Juan Luis Gonzalez Bello , Jaeho Moon , Jihyong Oh , Munchurl Kim

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

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

Semantic scene completion (SSC) requires an accurate understanding of the geometric and semantic relationships between the objects in the 3D scene for reasoning the occluded objects. The popular SSC methods voxelize the 3D objects, allowing…

Computer Vision and Pattern Recognition · Computer Science 2023-07-18 Haotian Dong , Enhui Ma , Lubo Wang , Miaohui Wang , Wuyuan Xie , Qing Guo , Ping Li , Lingyu Liang , Kairui Yang , Di Lin

3D Gaussian Splatting (3DGS) has recently emerged as a promising 3D representation. Much research has been focused on reducing its storage requirements and memory footprint. However, the needs to compress and transmit the 3DGS…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Yu-Ting Zhan , Cheng-Yuan Ho , Hebi Yang , Yi-Hsin Chen , Jui Chiu Chiang , Yu-Lun Liu , Wen-Hsiao Peng

3D Gaussian Splatting (3DGS) has become horsepower in high-quality, real-time rendering for novel view synthesis of 3D scenes. However, existing methods focus primarily on geometric and appearance modeling, lacking deeper scene…

Graphics · Computer Science 2025-07-01 Minchao Jiang , Shunyu Jia , Jiaming Gu , Xiaoyuan Lu , Guangming Zhu , Anqi Dong , Liang Zhang
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