EDBT 2026 Demo / reviewers in the wild / expert
Fanhuai Shi
dblp:50/3192
· DBLP profile ↗
12ranked-venue papers
4as first author
1since 2021 · last 2022
0000-0002-4282-4732ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 7 · 3 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 4 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 3 · 2 first-authorSystems, architecture and hardware · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Video understanding and tracking · 50% 3D vision · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Video understanding and tracking
motion segmentation |
0.1 | 1 | 2005 | Motion Segmentation of Multiple Translating Objects Using Line Correspondences · CVPR (1) 2005 |
Computer vision › Video understanding and tracking › motion segmentation
multi-body motion segmentation |
0.1 | 1 | 2005 | Motion Segmentation of Multiple Translating Objects Using Line Correspondences · CVPR (1) 2005 |
Computer vision › 3D vision
multi-view geometry |
0.1 | 1 | 2005 | Motion Segmentation of Multiple Translating Objects Using Line Correspondences · CVPR (1) 2005 |
Computer vision › 3D vision › multi-view geometry › multifocal tensor
trifocal tensor |
0.1 | 1 | 2005 | Motion Segmentation of Multiple Translating Objects Using Line Correspondences · CVPR (1) 2005 |
Methods — techniques the papers use, named apart from their topics
polynomial embedding · 0.1line correspondence · 0.1clustering · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | I2DKPCN: an unsupervised deep learning network
Ruyi Zhao, Fanhuai Shi |
Appl. Intell. | 2 |
| 2019 | A Welding Defect Identification Approach in X-ray Images Based on Deep Convolutional Neural Networks
Fanhuai Shi, Xuefeng Tong |
ICIC (3) | 2 |
| 2014 | A Rotation and Scale Invariant Approach for Dense Wide Baseline Matching
Jian Gao 0006, Fanhuai Shi |
ICIC (1) | 2 |
| 2013 | An Improved Image Corner Matching Approach
Bijin Yan, Fanhuai Shi, Jiguang Yue |
ICIC (1) | 2 |
| 2009 | SVM-based fuzzy rules acquisition system for pulsed GTAW process
Xixia Huang, Fanhuai Shi, Shan-Ben Chen |
Eng. Appl. Artif. Intell. | 2 |
| 2008 | A new calibration model of camera lens distortion
Fanhuai Shi, Jing Zhang 0007, Yuncai Liu |
Pattern Recognit. | 2 |
| 2006 | Camera Calibration from a Single Frame of Planar Pattern
Fanhuai Shi, Jing Zhang 0007, Yuncai Liu |
ACIVS | 2 |
| 2006 | A New Calibration Model and Method of Camera Lens DistortionabstractLens distortion is one of the main factors affecting camera calibration. In this paper, a new model of camera lens distortion is presented, according to which lens distortion is governed by the coefficients of radial distortion and a transform from ideal image plane to real sensing array plane. The transform is determined by two angular parameters describing the pose and two linear parameters locating the position of the sensing array plane. Compared with the conventional ones, the new model has fewer parameters to be calibrated and more explicit physical meaning. Calibration method of the new model is also proposed. Experiments show that calibration results from the new model and method can correct lens distortion better than conventional ones Fanhuai Shi, Jing Zhang 0007, Yuncai Liu |
IROS | 2 |
| 2005 | Motion Segmentation of Multiple Translating Objects Using Line CorrespondencesabstractWe present an algebraic approach to multibody motion segmentation from line correspondences. Given three perspective views containing multiple linearly moving objects, we demonstrate that after applying a polynomial embedding to the line correspondences, they became related by the so-called multibody line constraint of translational motions. We show how to linearly estimate the multibody trifocal epipole from line-line-line correspondences. The individual trifocal epipoles are then obtained from the derivatives of the multibody line constraint (up to an unknown factor). Given normalized trifocal epipoles, we can use any special clustering technique to obtain the clustering of the motions and the correspondences. The limitations of the proposed algorithm are also discussed. Experimental results on synthetic and real dynamic scenes are presented. Fanhuai Shi, Jing Zhang 0007, Yuncai Liu |
CVPR (1) | 1 |
| 2005 | A Hand-Eye Robotic Model for Total Knee Replacement Surgery
Fanhuai Shi, Jing Zhang 0007, Yuncai Liu |
MICCAI (2) | 1 |
| 2005 | Motion segmentation of multiple translating objects from line correspondences
Fanhuai Shi, Jing Zhang 0007, Yuncai Liu |
Pattern Recognit. | 1 |
| 2004 | A new method of camera pose estimation using 2D-3D corner correspondence
Fanhuai Shi, Xiaoyun Zhang 0003, Yuncai Liu |
Pattern Recognit. Lett. | 1 |