Dataset - DiVA: Wiki - Confluence

Dataset - Hull City Council Open Data

Fallen People Data Set (FPDS), a novel benchmark for detecting fallen people lying on the floor. It consists of 6982 images, with a total of 5023 falls and 2275 non falls corresponding to people in conventional situations. 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. Roboflow hosts free public computer vision datasets in many popular formats (including CreateML JSON, COCO JSON, Pascal VOC XML, YOLO v3, and Tensorflow TFRecords). For your convenience, we also have downsized and augmented versions available.

The PersonX dataset is generated by the synthetic data engine PersonX that can synthesise images under controllable cameras and environment. For researching viewpoint , six backgrounds are used in "Dissecting Person Re-identification from the Viewpoint of Viewpoint" (as shown in the following figure), including three pure color backgrounds and three scene backgrounds. detect person dlib. Test example detect person with dlib vector machine utility. Dataset INRIA person: http://pascal.inrialpes.fr/data/human/.

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The heights of labeled pedestrians in this COCO is a large-scale object detection, segmentation, and captioning dataset. 91 stuff categories; 5 captions per image; 250,000 people with keypoints Apr 6, 2020 available datasets are exclusively suitable for the pedestrian tection, Object Tracking, Person Re-identification, Person Search.

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Real . 27170754 . 115 . 2019

2019-05-31 2017-08-16 INRIA Person Data Set. INRIA Person Dataset. A large set of marked up images of standing or walking people, used to train Navneet Dalal's CVPR 2005 human detector. INRIA Car Data Set. INRIA Car Dataset. A set of car and non-car images taken in a parking lot nearby INRIA. Cross-Dataset Person Re-Identiﬁcation via Unsupervised Pose Disentanglement and Adaptation Yu-Jhe Li1,2,3, Ci-Siang Lin1,2, Yan-Bo Lin1, Yu-Chiang Frank Wang1,2,3 1National Taiwan University, Taiwan 2MOST Joint Research Center for AI Technology and All Vista Healthcare, Taiwan 3ASUS Intelligent Cloud Services, Taiwan {d08942008, d08942011, r06942048, ycwang}@ntu.edu.tw Pose Transferrable Person Re-Identiﬁcation Jinxian Liu1∗ Bingbing Ni1∗† Yichao Yan1∗ Peng Zhou1 Shuo Cheng1 Jianguo Hu2 1Shanghai Key Laboratory of Digital Media Processing and Transmission, Shanghai Institute for Advanced Communication and Data Science, Shanghai Jiao Tong University, Shanghai 200240, China This dataset includes 502,529 persons in Wikipedia. The person graph is extracted from DBpedia 2014, and represented as RDF triples, including their categories.
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We collected two separate datasets. The first dataset is collected using Kinect mounted on top of a humanoid robot.

Zhang to get the download link.) LS-VID dataset for video person re-id.
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The BP4D dataset includes videos of 41 participants (21 used for Multiple people; Socially interacting groups; 3D body pose; 3D facial landmarks; Transcripts 2016, The CMU PanopticStudio Dataset is now publicly released. 6 Mar 2020 Explore the Dataset; Model Test and Baseline Result; Evaluate Models; Make Prediction on New Data. Adult Income Dataset. 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.

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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.