Pedestrian drone dataset. Dec 19, 2015 · Stanford Aerial Pedestrian Dataset Introduction When humans navigate a crowed space such as a university campus or the sidewalks of a busy street, they follow common sense rules based on social etiquette. EuroCity Person Dataset WIDER Face and Pedestrian Challenge Cityscapes CityPersons PASCAL VOC TUGRAZ ICG Longterm Pedestrian Dataset Mall Dataset INRIA Person Dataset Crowd Dataset Caltech Pedestrian Detection Benchmark MIT ReforesTree -> A dataset for estimating tropical forest biomass based on drone and field data yosemite-tree-dataset -> a benchmark dataset for tree counting from aerial images LADD-utils is a set of utils and tools to convert and augument datasets for lacmus neural networks. Nov 26, 2020 · This paper announces the free availability of the P-DESTRE dataset, the first of its kind to provide video/UAV-based data for pedestrian long-term re-identification research, with ID annotations Oct 6, 2023 · We evaluate the proposed real-time on-drone pedestrian tracker with real-world drone-captured videos in the DNA+Drone dataset [15]. Sep 30, 2023 · PDF | An automation tool for Pedestrian Crossing Data extraction from inD drone dataset. Ideal for drone-based object detection, traffic analysis, and surveillance AI models. Existing datasets are either confined to 2D cases, exhibit limited geometric variations, or lack the multi‑modal annotations and data structures—shortcomings we address with AutoHood3D. Nov 6, 2025 · This work addresses critical challenges in multi-view pedestrian detection and tracking for dynamic drone-based surveillance through the introduction of the MATRIX dataset and a novel multi-view framework. This dataset simplifies the VisDrone2019 dataset by merging classes into compact categories for better classification performance. Introduced in our CVPR 2016 submission "Forecasting Social Navigation in Crowded Complex Scenes", the Stanford Aerial Pedestrian Dataset consists of annotated videos of pedestrians, bikers, skateboarders, cars, buses, and golf carts navigating eight unique scenes on the Stanford University campus. We’re on a journey to advance and democratize artificial intelligence through open source and open science. aoctlf iejra viuu qyykf cao zoj njsh udfoiul bdb xrrnal