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Related papers: Scene Grounding In the Wild

200 papers

Recently, 3D Gaussian Splatting (3DGS) has emerged as an efficient approach for accurately representing scenes. However, despite its superior novel view synthesis capabilities, extracting the geometry of the scene directly from the Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yaniv Wolf , Amit Bracha , Ron Kimmel

Reconstructing complete and interactive 3D scenes remains a fundamental challenge in computer vision and robotics, particularly due to persistent object occlusions and limited sensor coverage. Multiview observations from a single scene scan…

Computer Vision and Pattern Recognition · Computer Science 2025-08-19 Wenhao Hu , Zesheng Li , Haonan Zhou , Liu Liu , Xuexiang Wen , Zhizhong Su , Xi Li , Gaoang Wang

High-fidelity visual reconstruction and novel-view synthesis are essential for realistic closed-loop evaluation in autonomous driving. While 4D Gaussian Splatting (4DGS) offers a promising balance of accuracy and efficiency, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Haibao Yu , Kuntao Xiao , Jiahang Wang , Ruiyang Hao , Yuxin Huang , Guoran Hu , Haifang Qin , Bowen Jing , Yuntian Bo , Ping Luo

The scalability of embodied intelligence is fundamentally constrained by the scarcity of real-world interaction data. While simulation platforms provide a promising alternative, existing approaches often suffer from a substantial visual and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Zhengqing Gao , Ziwen Li , Xin Wang , Jiaxin Huang , Zhenyang Ren , Mingkai Shao , Hanlue Zhang , Tianyu Huang , Yongkang Cheng , Yandong Guo , Runqi Lin , Yuanyuan Wang , Tongliang Liu , Kun Zhang , Mingming Gong

In this study, we address the challenge of 3D scene structure recovery from monocular depth estimation. While traditional depth estimation methods leverage labeled datasets to directly predict absolute depth, recent advancements advocate…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Chi Zhang , Wei Yin , Gang Yu , Zhibin Wang , Tao Chen , Bin Fu , Joey Tianyi Zhou , Chunhua Shen

Modern scene reconstruction methods are able to accurately recover 3D surfaces that are visible in one or more images. However, this leads to incomplete reconstructions, missing all occluded surfaces. While much progress has been made on…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Sam Bahrami , Dylan Campbell

This paper presents DENSER, an efficient and effective approach leveraging 3D Gaussian splatting (3DGS) for the reconstruction of dynamic urban environments. While several methods for photorealistic scene representations, both implicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Mahmud A. Mohamad , Gamal Elghazaly , Arthur Hubert , Raphael Frank

We present a method to map 2D image observations of a scene to a persistent 3D scene representation, enabling novel view synthesis and disentangled representation of the movable and immovable components of the scene. Motivated by the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-11 Prafull Sharma , Ayush Tewari , Yilun Du , Sergey Zakharov , Rares Ambrus , Adrien Gaidon , William T. Freeman , Fredo Durand , Joshua B. Tenenbaum , Vincent Sitzmann

3D visual grounding has made notable progress in localizing objects within complex 3D scenes. However, grounding referring expressions beyond objects in 3D scenes remains unexplored. In this paper, we introduce Anywhere3D-Bench, a holistic…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Tianxu Wang , Zhuofan Zhang , Ziyu Zhu , Yue Fan , Jing Xiong , Pengxiang Li , Xiaojian Ma , Qing Li

Image-based localization, or camera relocalization, is a fundamental problem in computer vision and robotics, and it refers to estimating camera pose from an image. Recent state-of-the-art approaches use learning based methods, such as…

Computer Vision and Pattern Recognition · Computer Science 2018-06-26 Xiaotian Li , Juha Ylioinas , Juho Kannala

This paper presents GS-RoadPatching, an inpainting method for driving scene completion by referring to completely reconstructed regions, which are represented by 3D Gaussian Splatting (3DGS). Unlike existing 3DGS inpainting methods that…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Guo Chen , Jiarun Liu , Sicong Du , Chenming Wu , Deqi Li , Shi-Sheng Huang , Guofeng Zhang , Sheng Yang

Extracting planes from a 3D scene is useful for downstream tasks in robotics and augmented reality. In this paper we tackle the problem of estimating the planar surfaces in a scene from posed images. Our first finding is that a surprisingly…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Jamie Watson , Filippo Aleotti , Mohamed Sayed , Zawar Qureshi , Oisin Mac Aodha , Gabriel Brostow , Michael Firman , Sara Vicente

Representing and rendering dynamic scenes from 2D images is a fundamental yet challenging problem in computer vision and graphics. This survey provides a comprehensive review of the evolution and advancements in dynamic scene representation…

Graphics · Computer Science 2025-03-12 Jiaxuan Zhu , Hao Tang

In this work, we present Fed3DGS, a scalable 3D reconstruction framework based on 3D Gaussian splatting (3DGS) with federated learning. Existing city-scale reconstruction methods typically adopt a centralized approach, which gathers all…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Teppei Suzuki

We present SAM 3D, a generative model for visually grounded 3D object reconstruction, predicting geometry, texture, and layout from a single image. SAM 3D excels in natural images, where occlusion and scene clutter are common and visual…

Video diffusion models generate high-quality and diverse worlds; however, individual frames often lack 3D consistency across the output sequence, which makes the reconstruction of 3D worlds difficult. To this end, we propose a new method…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Lukas Höllein , Matthias Nießner

Production of photorealistic, navigable 3D site models requires a large volume of carefully collected images that are often unavailable to first responders for disaster relief or law enforcement. Real-world challenges include limited…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Neil Joshi , Joshua Carney , Nathanael Kuo , Homer Li , Cheng Peng , Myron Brown

We present a framework that enables fast reconstruction and real-time rendering of urban-scale scenes while maintaining robustness against appearance variations across multi-view captures. Our approach begins with scene partitioning for…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Zhensheng Yuan , Haozhi Huang , Zhen Xiong , Di Wang , Guanghua Yang

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) 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