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A novel image matching method is proposed that utilizes learned features extracted by an off-the-shelf deep neural network to obtain a promising performance. The proposed method uses pre-trained VGG architecture as a feature extractor and…

Computer Vision and Pattern Recognition · Computer Science 2021-06-16 Ufuk Efe , Kutalmis Gokalp Ince , A. Aydin Alatan

Feature-based visual structure and motion reconstruction pipelines, common in visual odometry and large-scale reconstruction from photos, use the location of corresponding features in different images to determine the 3D structure of the…

Robotics · Computer Science 2016-07-04 Pablo F. Alcantarilla , Oliver J. Woodford

Sub-image search with high accuracy in natural images still remains a challenging problem. This paper proposes a new feature vector called profile for a keypoint in a bag of visual words model of an image. The profile of a keypoint captures…

Computer Vision and Pattern Recognition · Computer Science 2010-10-08 Vishwakarma Singh , Ambuj K. Singh

Motion segmentation in dynamic scenes is highly challenging, as conventional methods heavily rely on estimating camera poses and point correspondences from inherently noisy motion cues. Existing statistical inference or iterative…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Xiankang He , Peile Lin , Ying Cui , Dongyan Guo , Chunhua Shen , Xiaoqin Zhang

We propose a novel pose estimation method for geometric vision of omni-directional cameras. On the basis of the regularity of the pixel movement after camera pose changes, we formulate and prove the sinusoidal relationship between pixels…

Robotics · Computer Science 2019-10-04 Haofei Kuang , Qingwen Xu , Xiaoling Long , Sören Schwertfeger

Establishing consistent correspondences across images is essential for 3D vision tasks such as structure-from-motion (SfM), yet most existing matchers operate in a pairwise manner, often producing fragmented and geometrically inconsistent…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Jongmin Lee , Seungyeop Kang , Sungjoo Yoo

State-of-the-art object detectors usually learn multi-scale representations to get better results by employing feature pyramids. However, the current designs for feature pyramids are still inefficient to integrate the semantic information…

Computer Vision and Pattern Recognition · Computer Science 2018-08-27 Tao Kong , Fuchun Sun , Wenbing Huang , Huaping Liu

The "lifting from 2D pose" method has been the dominant approach to 3D Human Pose Estimation (3DHPE) due to the powerful visual analysis ability of 2D pose estimators. Widely known, there exists a depth ambiguity problem when estimating…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Feng Zhou , Jianqin Yin , Peiyang Li

We present SyncFix, a framework that enforces cross-view consistency during the diffusion-based refinement of reconstructed scenes. SyncFix formulates refinement as a joint latent bridge matching problem, synchronizing distorted and clean…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Deming Li , Abhay Yadav , Cheng Peng , Rama Chellappa , Anand Bhattad

Pipe inspection is a critical task for many industries and infrastructure of a city. The 3D information of a pipe can be used for revealing the deformation of the pipe surface and position of the camera during the inspection. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2020-07-06 Sho kagami , Hajime Taira , Naoyuki Miyashita , Akihiko Torii , Masatoshi Okutomi

One of the fundamental problems in computer vision is the two-frame relative pose optimization problem. Primarily, two different kinds of error values are used: photometric error and re-projection error. The selection of error value is…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Andreas L. Teigen , Annette Stahl , Rudolf Mester

We study the problem of shape generation in 3D mesh representation from a small number of color images with or without camera poses. While many previous works learn to hallucinate the shape directly from priors, we adopt to further improve…

Computer Vision and Pattern Recognition · Computer Science 2022-04-22 Chao Wen , Yinda Zhang , Chenjie Cao , Zhuwen Li , Xiangyang Xue , Yanwei Fu

Integration of aerial and ground images has been proved as an efficient approach to enhance the surface reconstruction in urban environments. However, as the first step, the feature point matching between aerial and ground images is…

Computer Vision and Pattern Recognition · Computer Science 2020-11-24 Qing Zhu , Zhendong Wang , Han Hu , Linfu Xie , Xuming Ge , Yeting Zhang

Many objects, especially these made by humans, are symmetric, e.g. cars and aeroplanes. This paper addresses the estimation of 3D structures of symmetric objects from multiple images of the same object category, e.g. different cars, seen…

Computer Vision and Pattern Recognition · Computer Science 2016-09-23 Yuan Gao , Alan Yuille

We introduce a novel learning-based method to reconstruct the high-quality geometry and complex, spatially-varying BRDF of an arbitrary object from a sparse set of only six images captured by wide-baseline cameras under collocated point…

Computer Vision and Pattern Recognition · Computer Science 2020-07-07 Sai Bi , Zexiang Xu , Kalyan Sunkavalli , David Kriegman , Ravi Ramamoorthi

The implementation of a Structure-from-Motion (SfM) pipeline from a synthetically generated scene as well as the investigation of the faithfulness of diverse reconstructions is the subject of this project. A series of different SfM…

Computer Vision and Pattern Recognition · Computer Science 2017-10-04 Martin Hahner , Orestis Varesis , Panagiotis Bountouris

Non-Rigid Structure from Motion (NRSfM) refers to the problem of reconstructing cameras and the 3D point cloud of a non-rigid object from an ensemble of images with 2D correspondences. Current NRSfM algorithms are limited from two…

Computer Vision and Pattern Recognition · Computer Science 2019-09-10 Chen Kong , Simon Lucey

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

Infrared thermography has been widely used in several domains to capture and measure temperature distributions across surfaces and objects. This methodology can be further expanded to 3D applications if the spatial distribution of the…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Jincheng Zhang , Kevin Brink , Andrew R Willis

This paper proposes a two-view deterministic geometric model fitting method, termed Superpixel-based Deterministic Fitting (SDF), for multiple-structure data. SDF starts from superpixel segmentation, which effectively captures prior…

Computer Vision and Pattern Recognition · Computer Science 2016-07-21 Guobao Xiao , Hanzi Wang , Yan Yan , David Suter
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