Topic: svo Goto Github
Some thing interesting about svo
Some thing interesting about svo
svo,A GPU SVO Builder using rasterization pipeline, a efficient SVO ray marcher and a simple SVO path tracer.
User: adamyuan
svo,Subject-verb-object triplets extraction for russian language.
User: dmitry-rvn
svo,BlackPearl Rendering Engine
User: dxt00
svo,Java/LWJGL pathtracer based on the paper "Efficient Sparse Voxel Octrees" by Samuli Laine and Tero Karras.
User: dyoo47
svo,A SVO based SLAM implementation for stereo cameras
User: eichenberger
svo,Official implementation and dataset for the NAACL 2024 paper "ComCLIP: Training-Free Compositional Image and Text Matching"
Organization: eric-ai-lab
Home Page: https://sites.google.com/view/comclip
svo,Automatic SVO Extraction Tool for Social Science
User: hjian42
Home Page: https://pc-ace.com/about/team/
svo,A repo for the PlayStation Home SVML Tool
User: kobun42
svo,Hardware accelerated voxel ray marching
User: mitchellhansen
svo,Voxel rendering engine for master thesis (voxel skeletal animation)
User: nieznanysprawiciel
svo,The web contains vast repositories of unstructured text. We investigate the opportunity for building a knowledge graph from these text sources. We generate a set of triples which can be used in knowledge gathering and integration. We define the architecture of a language compiler for processing subject-predicate-object triples using the OpenNLP parser. We implement a depth-first search traversal on the POS tagged syntactic tree appending predicate and object information. A parser enables higher precision and higher recall extractions of syntactic relationships across conjunction boundaries. We are able to extract 2-2.5 times the correct extractions of ReVerb. The extractions are used in a variety of semantic web applications and question answering. We verify extraction of 50,000 triples on the ClueWeb dataset.
User: shaundsouza
Home Page: https://arxiv.org/abs/1811.05768
svo,This repository intends to enable autonomous drone delivery with the Intel Aero RTF drone and PX4 autopilot. The code can be executed both on the real drone or simulated on a PC using Gazebo. Its core is a robot operating system (ROS) node, which communicates with the PX4 autopilot through mavros. It uses SVO 2.0 for visual odometry, WhyCon for visual marker localization and Ewok for trajectoy planning with collision avoidance.
User: szebedy
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