Search Results for author: Ji Zhao

Found 15 papers, 1 papers with code

Globally Optimal and Efficient Vanishing Point Estimation in Atlanta World

no code implementations ECCV 2020 Haoang Li, Pyojin Kim, Ji Zhao, Kyungdon Joo, Zhipeng Cai, Zhe Liu , Yun-hui Liu

In Atlanta world, given a set of image lines, we aim to cluster them by the unknown-but-sought VPs whose number is unknown.

On Relative Pose Recovery for Multi-Camera Systems

no code implementations24 Feb 2021 Ji Zhao, Banglei Guan

This solver generation method is also naturally applied to relative pose estimation from PCs, resulting in a new six-point method for multi-camera systems.

Pose Estimation Translation

Hybrid Rotation Averaging: A Fast and Robust Rotation Averaging Approach

1 code implementation CVPR 2021 Yu Chen, Ji Zhao, Laurent Kneip

We push the envelope of rotation averaging by leveraging the advantages of a global RA method and a local RA method.

3D Reconstruction

Minimal Solutions for Relative Pose with a Single Affine Correspondence

no code implementations CVPR 2020 Banglei Guan, Ji Zhao, Zhang Li, Fang Sun, Friedrich Fraundorfer

In this paper we present four cases of minimal solutions for two-view relative pose estimation by exploiting the affine transformation between feature points and we demonstrate efficient solvers for these cases.

Motion Estimation Outlier Detection +1

An Evaluation of Feature Matchers for Fundamental Matrix Estimation

no code implementations26 Aug 2019 Jia-Wang Bian, Yu-Huan Wu, Ji Zhao, Yun Liu, Le Zhang, Ming-Ming Cheng, Ian Reid

According to this, we propose three high-quality matching systems and a Coarse-to-Fine RANSAC estimator.

An Efficient Solution to Non-Minimal Case Essential Matrix Estimation

no code implementations21 Mar 2019 Ji Zhao

In this paper, we propose a certifiably globally optimal and efficient solver for the $N$-point problem.

POI Semantic Model with a Deep Convolutional Structure

no code implementations18 Mar 2019 Ji Zhao, Meiyu Yu, Huan Chen, Boning Li, Lingyu Zhang, Qi Song, Li Ma, Hua Chai, Jieping Ye

An accurate similarity calculation is challenging since the mismatch between a query and a retrieval text may exist in the case of a mistyped query or an alias inquiry.

Unsupervised Learnable Sinogram Inpainting Network (SIN) for Limited Angle CT reconstruction

no code implementations9 Nov 2018 Ji Zhao, Zhiqiang Chen, Li Zhang, Xin Jin

In this paper, we propose a sinogram inpainting network (SIN) to solve limited-angle CT reconstruction problem, which is a very challenging ill-posed issue and of great interest for several clinical applications.

Medical Physics Image and Video Processing

Density-Based Region Search with Arbitrary Shape for Object Localization

no code implementations23 Oct 2014 Ji Zhao, Deyu Meng, Jiayi Ma

Typically, the region search methods project the score of a classifier into an image plane, and then search the region with the maximal score.

Weakly-Supervised Object Localization

Feature and Region Selection for Visual Learning

no code implementations20 Jul 2014 Ji Zhao, Lian-Tao Wang, Ricardo Cabral, Fernando de la Torre

There are four main benefits of our approach: (1) Our approach accommodates non-linear additive kernels such as the popular $\chi^2$ and intersection kernel; (2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; (3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; (4) we point out strong connections with multiple kernel learning and multiple instance learning approaches.

Action Recognition Multiple Instance Learning

FastMMD: Ensemble of Circular Discrepancy for Efficient Two-Sample Test

no code implementations12 May 2014 Ji Zhao, Deyu Meng

Taking advantage of sampling of Fourier transform, FastMMD decreases the time complexity for MMD calculation from $O(N^2 d)$ to $O(L N d)$, where $N$ and $d$ are the size and dimension of the sample set, respectively.

Robust Estimation of Nonrigid Transformation for Point Set Registration

no code implementations CVPR 2013 Jiayi Ma, Ji Zhao, Jinwen Tian, Zhuowen Tu, Alan L. Yuille

In the second step, we estimate the transformation using a robust estimator called L 2 E. This is the main novelty of our approach and it enables us to deal with the noise and outliers which arise in the correspondence step.

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