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Related papers: Proactive Scene Decomposition and Reconstruction

200 papers

The ability to accurately reconstruct the 3D facets of a scene is one of the key problems in robotic vision. However, even with recent advances with machine learning, there is no high-fidelity universal 3D reconstruction method for this…

Computer Vision and Pattern Recognition · Computer Science 2019-10-08 Bipul Islam , Ji Liu , Anthony Yezzi , Romeil Sandhu

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

Deformable 3D Gaussian Splatting (3D-GS) is limited by missing intermediate motion information due to the low temporal resolution of RGB cameras. To address this, we introduce the first approach combining event cameras, which capture…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Wenhao Xu , Wenming Weng , Yueyi Zhang , Ruikang Xu , Zhiwei Xiong

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

In complex missions such as search and rescue,robots must make intelligent decisions in unknown environments, relying on their ability to perceive and understand their surroundings. High-quality and real-time reconstruction enhances…

Robotics · Computer Science 2024-10-10 Zijun Xu , Rui Jin , Ke Wu , Yi Zhao , Zhiwei Zhang , Jieru Zhao , Fei Gao , Zhongxue Gan , Wenchao Ding

Scene reconstruction from multi-view images is a fundamental problem in computer vision and graphics. Recent neural implicit surface reconstruction methods have achieved high-quality results; however, editing and manipulating the 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Xiaoyang Lyu , Chirui Chang , Peng Dai , Yang-Tian Sun , Xiaojuan Qi

Robotics applications often rely on scene reconstructions to enable downstream tasks. In this work, we tackle the challenge of actively building an accurate map of an unknown scene using an RGB-D camera on a mobile platform. We propose a…

Robotics · Computer Science 2025-04-09 Liren Jin , Xingguang Zhong , Yue Pan , Jens Behley , Cyrill Stachniss , Marija Popović

Reconstructing large-scale dynamic scenes from visual observations is a fundamental challenge in computer vision, with critical implications for robotics and autonomous systems. While recent differentiable rendering methods such as Neural…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Jingkang Wang , Henry Che , Yun Chen , Ze Yang , Lily Goli , Sivabalan Manivasagam , Raquel Urtasun

3D scene reconstruction from stereo endoscopic video data is crucial for advancing surgical interventions. In this work, we present an online framework for online, dense 3D scene reconstruction and tracking, aimed at enhancing surgical…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Michel Hayoz , Christopher Hahne , Thomas Kurmann , Max Allan , Guido Beldi , Daniel Candinas , ablo Márquez-Neila , Raphael Sznitman

We propose ActiveSplat, an autonomous high-fidelity reconstruction system leveraging Gaussian splatting. Taking advantage of efficient and realistic rendering, the system establishes a unified framework for online mapping, viewpoint…

Robotics · Computer Science 2025-06-17 Yuetao Li , Zijia Kuang , Ting Li , Qun Hao , Zike Yan , Guyue Zhou , Shaohui Zhang

Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural implicit models, limitations persist: (i) Inadequate Scene…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Zeyu Yang , Hongye Yang , Zijie Pan , Li Zhang

The realistic reconstruction of street scenes is critical for developing real-world simulators in autonomous driving. Most existing methods rely on object pose annotations, using these poses to reconstruct dynamic objects and move them…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Zipei Ma , Junzhe Jiang , Yurui Chen , Li Zhang

Dynamic scene reconstruction from casual videos has seen recent remarkable progress. Numerous approaches have attempted to overcome the ill-posedness of the task by distilling priors from 2D foundational models and by imposing hand-crafted…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Narek Tumanyan , Samuel Rota Bulò , Denis Rozumny , Lorenzo Porzi , Adam Harley , Tali Dekel , Peter Kontschieder , Jonathon Luiten

We present MOSAIC-GS, a novel, fully explicit, and computationally efficient approach for high-fidelity dynamic scene reconstruction from monocular videos using Gaussian Splatting. Monocular reconstruction is inherently ill-posed due to the…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Svitlana Morkva , Maximum Wilder-Smith , Michael Oechsle , Alessio Tonioni , Marco Hutter , Vaishakh Patil

Reconstructing dynamic scenes with complex human-object interactions is a fundamental challenge in computer vision and graphics. Existing Gaussian Splatting methods either rely on human pose priors while neglecting dynamic objects, or…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Taewoo Kim , Suwoong Yeom , Jaehyun Pyun , Geonho Cha , Dongyoon Wee , Joonsik Nam , Yun-Seong Jeong , Kyeongbo Kong , Suk-Ju Kang

We present DrivingGaussian, an efficient and effective framework for surrounding dynamic autonomous driving scenes. For complex scenes with moving objects, we first sequentially and progressively model the static background of the entire…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Xiaoyu Zhou , Zhiwei Lin , Xiaojun Shan , Yongtao Wang , Deqing Sun , Ming-Hsuan Yang

Egocentric video is crucial for next-generation 4D scene reconstruction, with applications in AR/VR and embodied AI. However, reconstructing dynamic first-person scenes is challenging due to complex ego-motion, occlusions, and hand-object…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Tingxi Chen , Zhengxue Cheng , Houqiang Zhong , Su Wang , Rong Xie , Li Song

Dynamic scene reconstruction has garnered significant attention in recent years due to its capabilities in high-quality and real-time rendering. Among various methodologies, constructing a 4D spatial-temporal representation, such as 4D-GS,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Weiwei Cai , Weicai Ye , Peng Ye , Tong He , Tao Chen

Given an image of a natural scene, we are able to quickly decompose it into a set of components such as objects, lighting, shadows, and foreground. We can then envision a scene where we combine certain components with those from other…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Jocelin Su , Nan Liu , Yanbo Wang , Joshua B. Tenenbaum , Yilun Du

Generative models have demonstrated remarkable abilities in generating high-fidelity visual content. In this work, we explore how generative models can further be used not only to synthesize visual content but also to understand the…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Yanbo Wang , Justin Dauwels , Yilun Du