Suchergebnisse
Suchergebnisse:
This repository hosts the source code for OrienterNet, a research project by Meta Reality Labs. OrienterNet leverages the power of deep learning to provide accurate positioning of images using free and globally-available maps from OpenStreetMap.
4. Apr. 2023 · OrienterNet estimates the location and orientation of a query image by matching a neural Bird's-Eye View with open and globally available maps from OpenStreetMap, enabling anyone to localize anywhere such maps are available.
- arXiv:2304.02009 [cs.CV]
- CVPR 2023
أورينت نت - متابعات. بدون موافقة أمنية أو تأشيرة مسبقة.. نظام أسد يسهّل عملية التغلغل الشيعي بمناطقه. في خطوة جديدة لتسرع عملية التمدد الشيعي في مناطق أسد، أعلن القائم بالأعمال العراقي بدمشق ...
Towards localization. Humans can eas-ily orient themselves with basic 2D maps while state-of-the-art algorithms for visual localization require complex 3D cues. Ori-enterNet can localize an image using only compact maps from OpenStreetMap by matching Bird’s-Eye View and neural maps.
Differently, algorithms for visual localization mostly rely on complex 3D point clouds that are expensive to build, store, and maintain over time. We bridge this gap by introducing OrienterNet, the first deep neural network that can localize an image with sub-meter accuracy using the same 2D semantic maps that humans use.
4. Apr. 2023 · OrienterNet is the first deep neural network that can localize an image with sub-meter accuracy using the same 2D semantic maps that humans use, and generalizes to new datasets and pushes the state of the art in both robotics and AR scenarios.
OrienterNet: Visual Localization in 2D Public Maps With Neural Matching. Humans can orient themselves in their 3D environments using simple 2D maps. Differently, algorithms for visual localization mostly rely on complex 3D point clouds that are expensive to build, store, and maintain over time.
.jpg&q=orientnet&ck=A04D13C29A7C8D941563ADCC9EC9571D&idpp=rc&idpview=singleimage&form=rc2idp "orientnet2")
