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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

Image-based 3D reconstruction or 3D photogrammetry of small-scale objects including insects and biological specimens is challenging due to the use of high magnification lens with inherent limited depth of field, and the object's fine…

Computer Vision and Pattern Recognition · Computer Science 2019-12-09 Hengjia Li , Chuong Nguyen

Detecting objects in a two-dimensional setting is often insufficient in the context of real-life applications where the surrounding environment needs to be accurately recognized and oriented in three-dimension (3D), such as in the case of…

Computer Vision and Pattern Recognition · Computer Science 2019-07-23 Amir Hossein Raffiee , Humayun Irshad

Single visual object tracking from an unmanned aerial vehicle (UAV) poses fundamental challenges such as object occlusion, small-scale objects, background clutter, and abrupt camera motion. To tackle these difficulties, we propose to…

Computer Vision and Pattern Recognition · Computer Science 2022-02-28 Stéphane Vujasinović , Stefan Becker , Timo Breuer , Sebastian Bullinger , Norbert Scherer-Negenborn , Michael Arens

Robots rely on visual relocalization to estimate their pose from camera images when they lose track. One of the challenges in visual relocalization is repetitive structures in the operation environment of the robot. This calls for…

Computer Vision and Pattern Recognition · Computer Science 2024-10-08 Fereidoon Zangeneh , Leonard Bruns , Amit Dekel , Alessandro Pieropan , Patric Jensfelt

A video autoencoder is proposed for learning disentan- gled representations of 3D structure and camera pose from videos in a self-supervised manner. Relying on temporal continuity in videos, our work assumes that the 3D scene structure in…

Computer Vision and Pattern Recognition · Computer Science 2021-10-07 Zihang Lai , Sifei Liu , Alexei A. Efros , Xiaolong Wang

In this paper, we present a new approach for improving 3D point and line mapping regression for camera re-localization. Previous methods typically rely on feature matching (FM) with stored descriptors or use a single network to encode both…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 Bach-Thuan Bui , Huy-Hoang Bui , Yasuyuki Fujii , Dinh-Tuan Tran , Joo-Ho Lee

The problem of segmenting a given image into coherent regions is important in Computer Vision and many industrial applications require segmenting a known object into its components. Examples include identifying individual parts of a…

Computer Vision and Pattern Recognition · Computer Science 2013-05-17 Srimal Jayawardena , Di Yang , Marcus Hutter

Monocular 3D lane detection is a challenging task due to its lack of depth information. A popular solution is to first transform the front-viewed (FV) images or features into the bird-eye-view (BEV) space with inverse perspective mapping…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Shaofei Huang , Zhenwei Shen , Zehao Huang , Zi-han Ding , Jiao Dai , Jizhong Han , Naiyan Wang , Si Liu

In this paper, we propose a method for initial camera pose estimation from just a single image which is robust to viewing conditions and does not require a detailed model of the scene. This method meets the growing need of easy deployment…

Computer Vision and Pattern Recognition · Computer Science 2022-03-10 Matthieu Zins , Gilles Simon , Marie-Odile Berger

Numerous works have recently integrated 3D camera control into foundational text-to-video models, but the resulting camera control is often imprecise, and video generation quality suffers. In this work, we analyze camera motion from a first…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Sherwin Bahmani , Ivan Skorokhodov , Guocheng Qian , Aliaksandr Siarohin , Willi Menapace , Andrea Tagliasacchi , David B. Lindell , Sergey Tulyakov

Recently, breakthroughs in video modeling have allowed for controllable camera trajectories in generated videos. However, these methods cannot be directly applied to user-provided videos that are not generated by a video model. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 David Junhao Zhang , Roni Paiss , Shiran Zada , Nikhil Karnad , David E. Jacobs , Yael Pritch , Inbar Mosseri , Mike Zheng Shou , Neal Wadhwa , Nataniel Ruiz

High-precision localization is pivotal in underwater reinspection missions. Traditional localization methods like inertial navigation systems, Doppler velocity loggers, and acoustic positioning face significant challenges and are not…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Luyuan Peng , Hari Vishnu , Mandar Chitre , Yuen Min Too , Bharath Kalyan , Rajat Mishra , Soo Pieng Tan

Conventional single image based localization methods usually fail to localize a querying image when there exist large variations between the querying image and the pre-built scene. To address this, we propose an image-set querying based…

Computer Vision and Pattern Recognition · Computer Science 2015-09-22 Lei Deng , Siyuan Huang , Yueqi Duan , Baohua Chen , Jie Zhou

In this paper, we address the inverse problem of reconstructing a scene as well as the camera motion from the image sequence taken by an omni-directional camera. Our structure from motion results give sharp conditions under which the…

Computer Vision and Pattern Recognition · Computer Science 2007-08-21 Oliver Knill , Jose Ramirez-Herran

Real-time holistic scene understanding would allow machines to interpret their surrounding in a much more detailed manner than is currently possible. While panoptic image segmentation methods have brought image segmentation closer to this…

Computer Vision and Pattern Recognition · Computer Science 2022-04-04 Leevi Raivio , Esa Rahtu

This work presents a novel RGB-D SLAM approach to simultaneously segment, track and reconstruct the static background and large dynamic rigid objects that can occlude major portions of the camera view. Previous approaches treat dynamic…

Robotics · Computer Science 2022-01-17 Ran Long , Christian Rauch , Tianwei Zhang , Vladimir Ivan , Sethu Vijayakumar

Recent camera-based 3D object detection is limited by the precision of transforming from image to 3D feature spaces, as well as the accuracy of object localization within the 3D space. This paper aims to address such a fundamental problem…

Computer Vision and Pattern Recognition · Computer Science 2024-02-08 Chaoqun Wang , Yiran Qin , Zijian Kang , Ningning Ma , Ruimao Zhang

Event cameras are rapidly emerging as powerful vision sensors for 3D reconstruction, uniquely capable of asynchronously capturing per-pixel brightness changes. Compared to traditional frame-based cameras, event cameras produce sparse yet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Chuanzhi Xu , Haoxian Zhou , Langyi Chen , Haodong Chen , Zeke Zexi Hu , Zhicheng Lu , Ying Zhou , Vera Chung , Qiang Qu , Weidong Cai

We present a method to reconstruct the 3D trajectory of an airborne robotic system only from videos recorded with cameras that are unsynchronized, may feature rolling shutter distortion, and whose viewpoints are unknown. Our approach…

Robotics · Computer Science 2020-07-30 Jingtong Li , Jesse Murray , Dorina Ismaili , Konrad Schindler , Cenek Albl
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