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We present a novel method to reconstruct 3D scenes from images by leveraging deep dense monocular SLAM and fast uncertainty propagation. The proposed approach is able to 3D reconstruct scenes densely, accurately, and in real-time while…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Antoni Rosinol , John J. Leonard , Luca Carlone

Real objects that inhabit the physical world follow physical laws and thus behave plausibly during interaction with other physical objects. However, current methods that perform 3D reconstructions of real-world scenes from multi-view 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Yuqiu Liu , Jialin Song , Marissa Ramirez de Chanlatte , Rochishnu Chowdhury , Rushil Paresh Desai , Wuyang Chen , Daniel Martin , Michael W. Mahoney

Point clouds are a fundamental 3D representation in computer vision, enabling a wide range of perception tasks. However, real-world point clouds often suffer from degradations such as incompleteness, noise, outliers, and irregular density,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Haoqing Wu , Alexa Nawotki , Jochen Garcke

We present a novel framework to reconstruct complete 3D human shapes from a given target image by leveraging monocular unconstrained images. The objective of this work is to reproduce high-quality details in regions of the reconstructed…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Marco Pesavento , Marco Volino , Adrian Hilton

Accurate monocular metric depth estimation (MMDE) is crucial to solving downstream tasks in 3D perception and modeling. However, the remarkable accuracy of recent MMDE methods is confined to their training domains. These methods fail to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Luigi Piccinelli , Yung-Hsu Yang , Christos Sakaridis , Mattia Segu , Siyuan Li , Luc Van Gool , Fisher Yu

Representing scenes from multi-view images is a crucial task in computer vision with extensive applications. However, inherent photometric distortions in the camera imaging can significantly degrade image quality. Without accounting for…

Computer Vision and Pattern Recognition · Computer Science 2025-06-27 Weichen Dai , Kangcheng Ma , Jiaxin Wang , Kecen Pan , Yuhang Ming , Hua Zhang , Wanzeng Kong

Neural volumetric representations have become a widely adopted model for radiance fields in 3D scenes. These representations are fully implicit or hybrid function approximators of the instantaneous volumetric radiance in a scene, which are…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Yuval Bahat , Yuxuan Zhang , Hendrik Sommerhoff , Andreas Kolb , Felix Heide

Point cloud completion aims to recover the complete 3D shape of an object from partial observations. While approaches relying on synthetic shape priors achieved promising results in this domain, their applicability and generalizability to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Başak Melis Öcal , Maxim Tatarchenko , Sezer Karaoglu , Theo Gevers

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

Despite the impressive progress of telepresence systems for room-scale scenes with static and dynamic scene entities, expanding their capabilities to scenarios with larger dynamic environments beyond a fixed size of a few square-meters…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Leif Van Holland , Patrick Stotko , Stefan Krumpen , Reinhard Klein , Michael Weinmann

Reconstructing 3D objects from a single image is an intriguing but challenging problem. One promising solution is to utilize multi-view (MV) 3D reconstruction to fuse generated MV images into consistent 3D objects. However, the generated…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Yizheng Chen , Rengan Xie , Qi Ye , Sen Yang , Zixuan Xie , Tianxiao Chen , Rong Li , Yuchi Huo

Plenoptic cameras use arrays of micro-lenses to capture multiple views of the same scene in a single compound image. They enable refocusing on different planes and depth estimation. However, until now, all types of plenoptic computational…

Optics · Physics 2020-01-29 K. M. Sowa , M. P. Kujda , P. Korecki

Depth estimation plays a pivotal role in advancing human-robot interactions, especially in indoor environments where accurate 3D scene reconstruction is essential for tasks like navigation and object handling. Monocular depth estimation,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Siddiqui Muhammad Yasir , Hyunsik Ahn

We propose a novel model for 3D semantic completion from a single depth image, based on a single encoder and three separate generators used to reconstruct different geometric and semantic representations of the original and completed scene,…

Computer Vision and Pattern Recognition · Computer Science 2022-05-10 Yida Wang , David Joseph Tan , Nassir Navab , Federico Tombari

Panoramic imagery offers a full 360{\deg} field of view and is increasingly common in consumer devices. However, it introduces non-pinhole distortions that challenge joint pose estimation and 3D reconstruction. Existing feed-forward models,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Yijing Guo , Mengjun Chao , Luo Wang , Tianyang Zhao , Haizhao Dai , Yingliang Zhang , Jingyi Yu , Yujiao Shi

Plenoptic imaging is a novel optical technique for three-dimensional imaging in a single shot. It is enabled by the simultaneous measurement of both the location and the propagation direction of light in a given scene. In the standard…

The plenoptic camera can capture both angular and spatial information of the rays, enabling 3D reconstruction by single exposure. The geometry of the recovered scene structure is affected by the calibration of the plenoptic camera…

Computer Vision and Pattern Recognition · Computer Science 2016-08-17 Chunping Zhang , Zhe Ji , Qing Wang

Reconstructing deformable tissues from endoscopic videos is essential in many downstream surgical applications. However, existing methods suffer from slow rendering speed, greatly limiting their practical use. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Yifan Liu , Chenxin Li , Chen Yang , Yixuan Yuan

Volumetric depth map fusion based on truncated signed distance functions has become a standard method and is used in many 3D reconstruction pipelines. In this paper, we are generalizing this classic method in multiple ways: 1) Semantics:…

Computer Vision and Pattern Recognition · Computer Science 2020-06-03 Denys Rozumnyi , Ian Cherabier , Marc Pollefeys , Martin R. Oswald

Underwater scene reconstruction is a critical tech-nology for underwater operations, enabling the generation of 3D models from images captured by underwater platforms. However, the quality of underwater images is often degraded due to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Junhao Shi , Jisheng Xu , Jianping He , Zhiliang Lin
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