73 skills found · Page 1 of 3
gkjohnson / Three Mesh BvhA BVH implementation to speed up raycasting and enable spatial queries against three.js meshes.
BUAA-BDA / OpenHuFuOpenHuFu is an open-sourced data federation system to support collaborative queries over multi databases with security guarantee.
16EAGLE / GetSpatialDataAn R package 📦 making it easy to query, preview, download and preprocess multiple kinds of spatial data 🛰 via R. All beta.
InsightLab / PyMovePyMove is a Python library to simplify queries and visualization of trajectories and other spatial-temporal data
jnidzwetzki / BboxdbBBoxDB is a scalable, highly available, and distributed data store for multi-dimensional big data. The software supports operations like multi-dimensional range queries and spatial joins. In addition, data streams are supported.
harryprince / Geosparkbring sf to spark in production
buptxyb666 / QueryPoseThis is an official implementation of our NeurIPS 22 paper“QueryPose: Sparse Multi-Person Pose Regression via Spatial-Aware Part-Level Query”
jblindsay / KdtreeA pure Nim k-d tree implementation for efficient spatial querying of point data
Antymon / QuadtreeEfficient implementation of a QuadTree data structure for spatial querying (e.g. collision detection)
angrysky56 / Ast MCP ServerBy transforming source code into a queryable Semantic Graph and a structured AST, this tool bridges the gap between "reading text" and "understanding structure." For an AI assistant, it provides the "spatial" awareness needed to navigate deep dependencies without getting lost in large files.
pkvartsianyi / SpatioAn embedded spatial database designed for applications that need to store and query location-based data efficiently.
seuros / Activerecord PostgisPostGIS extension for ActiveRecord's PostgreSQL adapter. Adds spatial types and queries to Rails 8+ with zero configuration.
rnd-forests / Skyline QuerySimple implementation of spatial skyline query algorithms
k255 / Drill GisSpatial queries with Apache Drill
RayYoh / LaSSM[TCSVT‘26] LaSSM: Efficient Semantic-Spatial Query Decoding via Local Aggregation and State Space Models for 3D Instance Segmentation
dandoran / Spring Data Postgis GeospatialThis project uses spring boot 2, spring data, postgis, hibernate spatial and flyway to manage DDL changes. This example includes some sample data to grab amazon distribution centers close to a certain lat, long. This application uses several useful distance queries.
Silverfish94 / GeoConfirmed QGISQGIS plugin to query and visualize GeoConfirmed conflict geolocation data. Filter by keywords, factions, dates, and spatial criteria.
amazon-science / H3 IndexerThe h3-indexer is an open source package for indexing geospatial data using PySpark, Apache Sedona and the H3 hierarchical spatial indexing system. The h3-indexer maps any number of vector-type geospatial data sets to H3 grids for efficient spatial analysis and querying.
DataOceanLab / GLINA lightweight learned index for spatial range queries on complex geometries
mustansarfiaz / PS ARMAbstract. Person search is a challenging problem with various real- world applications, that aims at joint person detection and re-identification of a query person from uncropped gallery images. Although, previous study focuses on rich feature information learning, it’s still hard to re- trieve the query person due to the occurrence of appearance deformations and background distractors. In this paper, we propose a novel attention- aware relation mixer (ARM) module for person search, which exploits the global relation between different local regions within RoI of a per- son and make it robust against various appearance deformations and occlusion. The proposed ARM is composed of a relation mixer block and a spatio-channel attention layer. The relation mixer block introduces a spatially attended spatial mixing and a channel-wise attended channel mixing for effectively capturing discriminative relation features within an RoI. These discriminative relation features are further enriched by intro- ducing a spatio-channel attention where the foreground and background discriminability is empowered in a joint spatio-channel space. Our ARM module is generic and it does not rely on fine-grained supervisions or topological assumptions, hence being easily integrated into any Faster R-CNN based person search methods. Comprehensive experiments are performed on two challenging benchmark datasets: CUHK-SYSU [1] and PRW [2]. Our PS-ARM achieves state-of-the-art performance on both datasets. On the challenging PRW dataset, our PS-ARM achieves an absolute gain of 5% in the mAP score over SeqNet, while operating at a comparable speed
