논문8 [Paper Review] Visual SLAM algorithms: a survey from 2010 to 2016 논문 : Visual SLAM algorithms: a survey from 2010 to 2016 URL : ipsjcva.springeropen.com/articles/10.1186/s41074-017-0027-2 Visual SLAM algorithms: a survey from 2010 to 2016 SLAM is an abbreviation for simultaneous localization and mapping, which is a technique for estimating sensor motion and reconstructing structure in an unknown environment. Especially, Simultaneous Localization and Mapping (S.. 2021. 5. 1. [Paper Review] Unsupervised Learning of Depth and Ego-Motion from Video 논문 : Unsupervised Learning of Depth and Ego-Motion from Video (Sfm Learner) URL : arxiv.org/abs/1704.07813 Unsupervised Learning of Depth and Ego-Motion from Video We present an unsupervised learning framework for the task of monocular depth and camera motion estimation from unstructured video sequences. We achieve this by simultaneously training depth and camera pose estimation networks using t.. 2021. 5. 1. [Papers Review] Parallel Tracking and Mapping for Small AR Workspaces(PTAM) 논문 : Parallel Tracking and Mapping for Small AR Workspaces (PTAM) URL : ieeexplore.ieee.org/document/4538852 Parallel Tracking and Mapping for Small AR Workspaces This paper presents a method of estimating camera pose in an unknown scene. While this has previously been attempted by adapting SLAM algorithms developed for robotic exploration, we propose a system specifically designed to track a ha.. 2021. 5. 1. [Papers Review] ArcFace: Additive Angular Margin Loss for Deep Face Recognition 논문 : ArcFace: Additive Angular Margin Loss for Deep Face Recognition(2019) , CVPR URL : https://arxiv.org/abs/1801.07698 ArcFace: Additive Angular Margin Loss for Deep Face Recognition One of the main challenges in feature learning using Deep Convolutional Neural Networks (DCNNs) for large-scale face recognition is the design of appropriate loss functions that enhance discriminative power. Centr.. 2020. 10. 11. 이전 1 2 다음 반응형
