Market-1501 is a large-scale public benchmark dataset for person re-identification. It contains 1501 identities which are captured by six different cameras, and 32,668 pedestrian image bounding-boxes obtained using the Deformable Part Models pedestrian detector. Each person has 3.6 images on average at each viewpoint.
The dataset is an order of magnitude larger and more challenge than similar previous attempts that contains 50,000 images with elaborated pixel-wise annotations with 19 semantic human part labels and 2D human poses with 16 key points. We prepared a dataset for addressing the false positives that occur during the person detection process. Some objects have very similar features to those of a person. If a model is trained using a dataset containing only persons, it leads to several false positives since it cannot differentiate such objects from that of a person. Labelme: A large dataset created by the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) containing 187,240 images, 62,197 annotated images, and 658,992 labeled objects. Lego Bricks: Approximately 12,700 images of 16 different Lego bricks classified by folders and computer rendered using Blender. The dataset is composed of image files and annotation files.
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Mohamed Elfeki, Krishna Regmi, Shervin Ardeshir, Ali Borji. First- person Audio-visual dataset consisting of short clips of human speech, extracted from interview videos uploaded to YouTube. This dataset contains 7,000 + speakers, 1 The central individual identifier across time is pid, which is fixed over time (and of course datasets). Since a person might change the household in which he or we propose a multispectral pedestrian dataset which pro- vides well aligned color-thermal image pairs, captured by beam splitter-based special hardware. Dec 24, 2015 INRIA Person Dataset · Caltech Pedestrian Detection Benchmark · MIT Pedestrian Dataset · UJ Pedestrian Dataset for human detection · Daimler Oct 26, 2019 Note: This video shows the PROX reference data obtained by fitting to RGB-D. This does not show the results of PROX on RGB. The goal of this Apr 18, 2020 Mask/Binary Annotation.
The KAIST Multispectral Pedestrian Dataset consists of 95k color-thermal pairs ( 640x480, 20Hz) taken from a vehicle.
2021-03-01 · For the task of detecting casualties and persons in search and rescue scenarios in drone images and videos, our database called SARD was built. The actors in the footage have simulate exhausted and injured persons as well as "classic" types of movement of people in nature, such as running, walking, standing, sitting, or lying down.
In both data, we isolate the egocentric camera holder in the third person video and thus, collect videos in which there is only a single person recorded by an This new dataset will help us have a deeper understanding of the fundamental problems in person re-ID. Our research also provides useful insights for dataset building and future practical usage. Note that GPR+ will be released with a open source license to enable further developments in person re-identification in the next few months.
Occlusion-Person Dataset Overview. This dataset is part our work AdaFuse: Adaptive Multiview Fusion for Accurate Human Pose Estimation in the Wild which is published on IJCV. The paper is available at (arXiv:2010.13302). Fig 1 Human models we used in Occlusion-Person
Similar to PRW dataset, the person search dataset is large scale dataset with full frame access and large amount of labeled bounding boxes.
It is a 4 camera dataset with 2 indoor and 2 outdoor cameras. JPL First-Person Interaction dataset (JPL-Interaction dataset) is composed of human activity videos taken from a first-person viewpoint. The dataset particularly
The VIRAT Video Dataset is designed to be realistic, natural and challenging for and human activity/event categories than existing action recognition datasets. Dataset. Note: To access the person reid datasets, please send mail to Prof. Zhang to get the download link.) LS-VID dataset for video person re-id. Download scientific diagram | Some human examples of the INRIA person dataset .
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In this project, we This dataset contains 5 different collective activities : crossing, walking, waiting, was annotated with image location of person, activity id, and pose direction. Karlsruhe Dataset: Labeled Objects (Cars + Pedestrians). This page contains objects_2011_a.zip: 775 images with car and pedestrian labels. This dataset 17 Mar 2019 IBM narrowed that dataset down to about 1 million photos of faces that have each been annotated, using automated coding and human 14 Apr 2017 Essentially, this massive data allows us to create highly accurate emotion metrics and provides us with fascinating insights into human emotional 18 May 2016 An updated translation of this dataset is in progress.
Each person has 3.6 images on average at each viewpoint. The Gallagher Collection Person Dataset Most face recognition databases contain images of faces shot under lab conditions. My collection is a set of typical digital image snapshots, captured in real life at real events of real people with real expressions. Since there is no existing person dataset supporting this new research direction, we propose a large-scale person description dataset with language annotations on detailed information of person images from various sources.
This dataset provides automatically extracted relations obtained using the algorithm in Faruqui and Kumar (2015) and the human annotations for evaluating the
Fig 1 Human models we used in Occlusion-Person The pose estimation problem belongs to a category of rather complex problems. Building a suitable dataset for neural network models is hard.
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CrowdHuman is a benchmark dataset to better evaluate detectors in crowd scenarios. The CrowdHuman dataset is large, rich-annotated and contains high diversity. CrowdHuman contains 15000, 4370 and 5000 images for training, validation, and testing, respectively. There are a total of 470K human instances from train and validation subsets and 23 persons per image, with various kinds of occlusions in the dataset.
Animal fats supply, per person, per day, calories, 1961–2013 Animal products supply, per person, per day, calories, 1961–2013 Cereals supply, per person, per day, calories, 1961–2013 Dietary fat consumption, per person, per day, grams, 1990–2007 This new dataset will help us have a deeper understanding of the fundamental problems in person re-ID. Our research also provides useful insights for dataset building and future practical usage. Note that GPR+ will be released with a open source license to enable further developments in person re-identification in the next few months. Yes, it is. The dataset was entirely copied in November 2015. KasparBot will remove all transclusions but there is nothing to be said against doing it manually.
The CrowdHuman dataset is large, rich-annotated and contains high diversity. CrowdHuman contains 15000, 4370 and 5000 images for training, validation, and testing, respectively. There are a total of 470K human instances from train and validation subsets and 23 persons per image, with various kinds of occlusions in the dataset.
We collected two separate datasets. The first dataset is collected using Kinect mounted on top of a humanoid robot.
Dataset Overview 1. Overview. Look into Person (LIP) is a new large-scale dataset, focus on semantic understanding of person. Following are the detailed descriptions. 1.1 Volume.