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Accurate camera models are essential for photogrammetry applications such as 3D mapping and object localization, particularly for long distances. Various stereo-camera based 3D localization methods are available but are limited to few…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Ami Pandat , Punna Rajasekhar , G. Aravamuthan , Gopika Vinod , Rohit Shukla

In recent years, the field of autonomous driving has witnessed remarkable advancements, driven by the integration of a multitude of sensors, including cameras and LiDAR systems, in different prototypes. However, with the proliferation of…

Computer Vision and Pattern Recognition · Computer Science 2023-10-10 Irene Cortés , Jorge Beltrán , Arturo de la Escalera , Fernando García

Solving the challenging problem of 3D object reconstruction from a single image appropriately gives existing technologies the ability to perform with a single monocular camera rather than requiring depth sensors. In recent years, thanks to…

Computer Vision and Pattern Recognition · Computer Science 2021-08-18 Guiju Ping , Mahdi Abolfazli Esfahani , Han Wang

We propose DepR, a depth-guided single-view scene reconstruction framework that integrates instance-level diffusion within a compositional paradigm. Instead of reconstructing the entire scene holistically, DepR generates individual objects…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Qingcheng Zhao , Xiang Zhang , Haiyang Xu , Zeyuan Chen , Jianwen Xie , Yuan Gao , Zhuowen Tu

Depth sensing is a critical component of autonomous driving technologies, but today's LiDAR- or stereo camera-based solutions have limited range. We seek to increase the maximum range of self-driving vehicles' depth perception modules for…

Computer Vision and Pattern Recognition · Computer Science 2020-04-08 Kai Zhang , Jiaxin Xie , Noah Snavely , Qifeng Chen

Reconstruction of a 3D shape from a single 2D image is a classical computer vision problem, whose difficulty stems from the inherent ambiguity of recovering occluded or only partially observed surfaces. Recent methods address this challenge…

Computer Vision and Pattern Recognition · Computer Science 2020-02-04 Yuan Yao , Nico Schertler , Enrique Rosales , Helge Rhodin , Leonid Sigal , Alla Sheffer

Imaging through thick scattering media presents significant challenges, particularly for three-dimensional (3D) applications. This manuscript demonstrates a novel scheme for single-image-enabled 3D imaging through such media, treating the…

Optics · Physics 2024-10-10 Long Pan , Yunan Wang , Yijie Lou , Xiaohua Feng

Deep learning techniques have enabled rapid progress in monocular depth estimation, but their quality is limited by the ill-posed nature of the problem and the scarcity of high quality datasets. We estimate depth from a single camera by…

Computer Vision and Pattern Recognition · Computer Science 2019-08-15 Rahul Garg , Neal Wadhwa , Sameer Ansari , Jonathan T. Barron

Surgical instrument tracking is an active research area that can provide surgeons feedback about the location of their tools relative to anatomy. Recent tracking methods are mainly divided into two parts: segmentation and object detection.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Ange Lou , Xing Yao , Ziteng Liu , Jintong Han , Jack Noble

We present WorldMirror, an all-in-one, feed-forward model for versatile 3D geometric prediction tasks. Unlike existing methods constrained to image-only inputs or customized for a specific task, our framework flexibly integrates diverse…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Yifan Liu , Zhiyuan Min , Zhenwei Wang , Junta Wu , Tengfei Wang , Yixuan Yuan , Yawei Luo , Chunchao Guo

Today, Multi-View Stereo techniques are able to reconstruct robust and detailed 3D models, especially when starting from high-resolution images. However, there are cases in which the resolution of input images is relatively low, for…

Computer Vision and Pattern Recognition · Computer Science 2021-07-29 Eugenio Lomurno , Andrea Romanoni , Matteo Matteucci

In this paper, we present a Mirroring Neural Network architecture to perform non-linear dimensionality reduction and Object Recognition using a reduced lowdimensional characteristic vector. In addition to dimensionality reduction, the…

Computer Vision and Pattern Recognition · Computer Science 2008-12-13 Dasika Ratna Deepthi , Sujeet Kuchibhotla , K. Eswaran

3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics. It is an ill-posed inverse problem, since -- without…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Edith Tretschk , Navami Kairanda , Mallikarjun B R , Rishabh Dabral , Adam Kortylewski , Bernhard Egger , Marc Habermann , Pascal Fua , Christian Theobalt , Vladislav Golyanik

Synthesizing accurate geometry and photo-realistic appearance of small scenes is an active area of research with compelling use cases in gaming, virtual reality, robotic-manipulation, autonomous driving, convenient product capture, and…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Arkadeep Narayan Chaudhury , Igor Vasiljevic , Sergey Zakharov , Vitor Guizilini , Rares Ambrus , Srinivasa Narasimhan , Christopher G. Atkeson

Capturing and reconstructing a human actor's motion is important for filmmaking and gaming. Currently, motion capture systems with static cameras are used for pixel-level high-fidelity reconstructions. Such setups are costly, require…

Robotics · Computer Science 2023-08-02 Qingyuan Jiang , Volkan Isler

Aiming at inferring 3D shapes from 2D images, 3D shape reconstruction has drawn huge attention from researchers in computer vision and deep learning communities. However, it is not practical to assume that 2D input images and their…

Computer Vision and Pattern Recognition · Computer Science 2018-11-30 Yi-Lun Liao , Yao-Cheng Yang , Yu-Chiang Frank Wang

Structure from Motion (SfM) often fails to estimate accurate poses in environments that lack suitable visual features. In such cases, the quality of the final 3D mesh, which is contingent on the accuracy of those estimates, is reduced. One…

Computer Vision and Pattern Recognition · Computer Science 2021-04-08 Victor Amblard , Timothy P. Osedach , Arnaud Croux , Andrew Speck , John J. Leonard

Accurate depth estimation is at the core of many applications in computer graphics, vision, and robotics. Current state-of-the-art monocular depth estimators, trained on extensive datasets, generalize well but lack 3D consistency needed for…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Laura Fink , Linus Franke , Bernhard Egger , Joachim Keinert , Marc Stamminger

In current practice, scene survey is carried out by workers using total stations. The method has high accuracy, but it incurs high costs if continuous monitoring is needed. Techniques based on photogrammetry, with the relatively cheaper…

Computer Vision and Pattern Recognition · Computer Science 2021-11-11 Kwok-Leung Chan , Liping Li , Arthur Wing-Tak Leung , Ho-Yin Chan

Precise calibration is a must for high reliance 3D computer vision algorithms. A challenging case is when the camera is behind a protective glass or transparent object: due to refraction, the image is heavily distorted; the pinhole camera…

Computer Vision and Pattern Recognition · Computer Science 2019-09-25 Szabolcs Pável , Csanád Sándor , Lehel Csató