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3-D pose estimation of instruments is a crucial step towards automatic scene understanding in robotic minimally invasive surgery. Although robotic systems can potentially directly provide joint values, this information is not commonly…

Robotics · Computer Science 2021-03-02 Luca Sestini , Benoit Rosa , Elena De Momi , Giancarlo Ferrigno , Nicolas Padoy

We revisit scene-level 3D object detection as the output of an object-centric framework capable of both localization and mapping using 3D oriented boxes as the underlying geometric primitive. While existing 3D object detection approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Justin Lazarow , Kai Kang , Afshin Dehghan

Real-world relations among entities can often be observed and determined by different perspectives/views. For example, the decision made by a user on whether to adopt an item relies on multiple aspects such as the contextual information of…

Machine Learning · Computer Science 2018-02-16 Chun-Ta Lu , Lifang He , Hao Ding , Bokai Cao , Philip S. Yu

Capturing the shape and spatially-varying appearance (SVBRDF) of an object from images is a challenging task that has applications in both computer vision and graphics. Traditional optimization-based approaches often need a large number of…

Computer Vision and Pattern Recognition · Computer Science 2021-05-20 Mark Boss , Varun Jampani , Kihwan Kim , Hendrik P. A. Lensch , Jan Kautz

A proper scene representation is central to the pursuit of spatial intelligence where agents can robustly reconstruct and efficiently understand 3D scenes. A scene representation is either metric, such as landmark maps in 3D reconstruction,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Juexiao Zhang , Gao Zhu , Sihang Li , Xinhao Liu , Haorui Song , Xinran Tang , Chen Feng

Novel View Synthesis (NVS) has traditionally relied on models with explicit 3D inductive biases combined with known camera parameters from Structure-from-Motion (SfM) beforehand. Recent vision foundation models like VGGT take an orthogonal…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Youming Deng , Songyou Peng , Junyi Zhang , Kathryn Heal , Tiancheng Sun , John Flynn , Steve Marschner , Lucy Chai

Accurate 3D reconstruction is frequently hindered by visual aliasing, where visually similar but distinct surfaces (aka, doppelgangers), are incorrectly matched. These spurious matches distort the structure-from-motion (SfM) process,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Yuanbo Xiangli , Ruojin Cai , Hanyu Chen , Jeffrey Byrne , Noah Snavely

Analysing 88 sources published from 2011 to 2021, this paper presents a first systematic review of the computer vision-based analysis of buildings and the built environments to assess its value to architectural and urban design studies.…

Computer Vision and Pattern Recognition · Computer Science 2022-08-02 Małgorzata B. Starzyńska , Robin Roussel , Sam Jacoby , Ali Asadipour

We present a real-time approach for image-based localization within large scenes that have been reconstructed offline using structure from motion (Sfm). From monocular video, our method continuously computes a precise 6-DOF camera pose, by…

Computer Vision and Pattern Recognition · Computer Science 2015-03-20 Hyon Lim , Sudipta Sinha , Michael Cohen , Matt Uyttendaele

Routine and repetitive infrastructure inspections present safety, efficiency, and consistency challenges as they are performed manually, often in challenging or hazardous environments. They can also introduce subjectivity and errors into…

Robotics · Computer Science 2025-01-28 Jake McLaughlin , Nicholas Charron , Sriram Narasimhan

We describe a data-driven method for inferring the camera viewpoints given multiple images of an arbitrary object. This task is a core component of classic geometric pipelines such as SfM and SLAM, and also serves as a vital pre-processing…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Jason Y. Zhang , Deva Ramanan , Shubham Tulsiani

Statistical shape modeling (SSM) is an enabling quantitative tool to study anatomical shapes in various medical applications. However, directly using 3D images in these applications still has a long way to go. Recent deep learning methods…

Computer Vision and Pattern Recognition · Computer Science 2023-10-04 Abu Zahid Bin Aziz , Jadie Adams , Shireen Elhabian

Nowadays stock photo agencies often have millions of images. Non-stop viewing of 20 million images at a speed of 10 images per second would take more than three weeks. This demonstrates the impossibility to inspect all images and the…

Multimedia · Computer Science 2019-10-15 Kai Uwe Barthel , Nico Hezel , Konstantin Schall , Klaus Jung

The pose graph is a core component of Structure-from-Motion (SfM), where images act as nodes and edges encode relative poses. Since geometric verification is expensive, SfM pipelines restrict the pose graph to a sparse set of candidate…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Tong Wei , Giorgos Tolias , Jiri Matas , Daniel Barath

Construction robots operate in unstructured construction sites, where effective visual perception is crucial for ensuring safe and seamless operations. However, construction robots often handle large elements and perform tasks across…

Robotics · Computer Science 2024-12-17 Jia Xu , Manish Dixit , Xi Wang

Accurate camera pose estimation from an image observation in a previously mapped environment is commonly done through structure-based methods: by finding correspondences between 2D keypoints on the image and 3D structure points in the map.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Fereidoon Zangeneh , Leonard Bruns , Amit Dekel , Alessandro Pieropan , Patric Jensfelt

In this paper, we present a robust and efficient Structure from Motion pipeline for accurate 3D reconstruction under challenging environments by leveraging the camera pose information from a visual-inertial odometry. Specifically, we…

Computer Vision and Pattern Recognition · Computer Science 2021-01-27 Zijie Jiang , Hajime Taira , Naoyuki Miyashita , Masatoshi Okutomi

We propose a new method named OnePose for object pose estimation. Unlike existing instance-level or category-level methods, OnePose does not rely on CAD models and can handle objects in arbitrary categories without instance- or…

Computer Vision and Pattern Recognition · Computer Science 2022-05-25 Jiaming Sun , Zihao Wang , Siyu Zhang , Xingyi He , Hongcheng Zhao , Guofeng Zhang , Xiaowei Zhou

Creating machines capable of understanding the world in 3D is essential in assisting designers that build and edit 3D environments and robots navigating and interacting within a three-dimensional space. Inspired by advances in language and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-07 Aadarsh Sahoo , Vansh Tibrewal , Georgia Gkioxari

Structure from Motion (SfM) techniques are being increasingly used to create 3D maps from images in many domains including environmental monitoring. However, SfM techniques are often confounded in visually repetitive environments as they…

Robotics · Computer Science 2022-01-11 Brian M. Hopkinson , Suchendra M. Bhandarkar
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