Search Results for author: Xiaotian Li

Found 7 papers, 1 papers with code

Digging Into Self-Supervised Learning of Feature Descriptors

no code implementations10 Oct 2021 Iaroslav Melekhov, Zakaria Laskar, Xiaotian Li, Shuzhe Wang, Juho Kannala

Fully-supervised CNN-based approaches for learning local image descriptors have shown remarkable results in a wide range of geometric tasks.

Image-Based Localization Image Retrieval +2

Continual Learning for Image-Based Camera Localization

1 code implementation ICCV 2021 Shuzhe Wang, Zakaria Laskar, Iaroslav Melekhov, Xiaotian Li, Juho Kannala

For several emerging technologies such as augmented reality, autonomous driving and robotics, visual localization is a critical component.

Autonomous Driving Camera Localization +2

Infrastructure Assisted Constrained Connected Automated Vehicle Trajectory Optimization on Curved Roads: A Spatial Formulation on a Curvilinear Coordinate

no code implementations1 Mar 2021 Ran Yi, Yang Zhou, Xin Wang, Zhiyuan Liu, Xiaotian Li, Bin Ran

This paper presents an infrastructure assisted constrained connected automated vehicles (CAVs) trajectory optimization method on curved roads.

Can You Trust Your Pose? Confidence Estimation in Visual Localization

no code implementations1 Oct 2020 Luca Ferranti, Xiaotian Li, Jani Boutellier, Juho Kannala

Camera pose estimation in large-scale environments is still an open question and, despite recent promising results, it may still fail in some situations.

Autonomous Navigation Pose Estimation +1

Hierarchical Scene Coordinate Classification and Regression for Visual Localization

no code implementations CVPR 2020 Xiaotian Li, Shuzhe Wang, Yi Zhao, Jakob Verbeek, Juho Kannala

In this work, we present a new hierarchical scene coordinate network to predict pixel scene coordinates in a coarse-to-fine manner from a single RGB image.

Classification Data Augmentation +2

Full-Frame Scene Coordinate Regression for Image-Based Localization

no code implementations9 Feb 2018 Xiaotian Li, Juha Ylioinas, Juho Kannala

In this paper, instead of in a patch-based manner, we propose to perform the scene coordinate regression in a full-frame manner to make the computation efficient at test time and, more importantly, to add more global context to the regression process to improve the robustness.

Camera Relocalization Data Augmentation +1

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